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- All Subjects: Mechanical Engineering
- Creators: Wang, Robert
- Creators: Ren, Yi
Description
Nanostructured materials show signicant enhancement in the thermoelectric g-
ure of merit (zT) due to quantum connement eects. Improving the eciency of
thermoelectric devices allows for the development of better, more economical waste
heat recovery systems. Such systems may be used as bottoming or co-generation
cycles in conjunction with conventional power cycles to recover some of the wasted
heat. Thermal conductivity measurement systems are an important part of the char-
acterization processes of thermoelectric materials. These systems must possess the
capability of accurately measuring the thermal conductivity of both bulk and thin-lm
samples at dierent ambient temperatures.
This paper discusses the construction, validation, and improvement of a thermal
conductivity measurement platform based on the 3-Omega technique. Room temperature
measurements of thermal conductivity done on control samples with known properties
such as undoped bulk silicon (Si), bulk gallium arsenide (GaAs), and silicon dioxide
(SiO2) thin lms yielded 150 W=m􀀀K, 50 W=m􀀀K, and 1:46 W=m􀀀K respectively.
These quantities were all within 8% of literature values. In addition, the thermal
conductivity of bulk SiO2 was measured as a function of temperature in a Helium-
4 cryostat from 75K to 250K. The results showed good agreement with literature
values that all fell within the error range of each measurement. The uncertainty in
the measurements ranged from 19% at 75K to 30% at 250K. Finally, the system
was used to measure the room temperature thermal conductivity of a nanocomposite
composed of cadmium selenide, CdSe, nanocrystals in an indium selenide, In2Se3,
matrix as a function of the concentration of In2Se3. The observed trend was in
qualitative agreement with the expected behavior.
i
ure of merit (zT) due to quantum connement eects. Improving the eciency of
thermoelectric devices allows for the development of better, more economical waste
heat recovery systems. Such systems may be used as bottoming or co-generation
cycles in conjunction with conventional power cycles to recover some of the wasted
heat. Thermal conductivity measurement systems are an important part of the char-
acterization processes of thermoelectric materials. These systems must possess the
capability of accurately measuring the thermal conductivity of both bulk and thin-lm
samples at dierent ambient temperatures.
This paper discusses the construction, validation, and improvement of a thermal
conductivity measurement platform based on the 3-Omega technique. Room temperature
measurements of thermal conductivity done on control samples with known properties
such as undoped bulk silicon (Si), bulk gallium arsenide (GaAs), and silicon dioxide
(SiO2) thin lms yielded 150 W=m􀀀K, 50 W=m􀀀K, and 1:46 W=m􀀀K respectively.
These quantities were all within 8% of literature values. In addition, the thermal
conductivity of bulk SiO2 was measured as a function of temperature in a Helium-
4 cryostat from 75K to 250K. The results showed good agreement with literature
values that all fell within the error range of each measurement. The uncertainty in
the measurements ranged from 19% at 75K to 30% at 250K. Finally, the system
was used to measure the room temperature thermal conductivity of a nanocomposite
composed of cadmium selenide, CdSe, nanocrystals in an indium selenide, In2Se3,
matrix as a function of the concentration of In2Se3. The observed trend was in
qualitative agreement with the expected behavior.
i
ContributorsJaber, Abbas (Author) / Wang, Robert (Thesis advisor) / Wang, Liping (Committee member) / Rykaczewski, Konrad (Committee member) / Arizona State University (Publisher)
Created2014
Description
Design problem formulation is believed to influence creativity, yet it has received only modest attention in the research community. Past studies of problem formulation are scarce and often have small sample sizes. The main objective of this research is to understand how problem formulation affects creative outcome. Three research areas are investigated: development of a model which facilitates capturing the differences among designers' problem formulation; representation and implication of those differences; the relation between problem formulation and creativity.
This dissertation proposes the Problem Map (P-maps) ontological framework. P-maps represent designers' problem formulation in terms of six groups of entities (requirement, use scenario, function, artifact, behavior, and issue). Entities have hierarchies within each group and links among groups. Variables extracted from P-maps characterize problem formulation.
Three experiments were conducted. The first experiment was to study the similarities and differences between novice and expert designers. Results show that experts use more abstraction than novices do and novices are more likely to add entities in a specific order. Experts also discover more issues.
The second experiment was to see how problem formulation relates to creativity. Ideation metrics were used to characterize creative outcome. Results include but are not limited to a positive correlation between adding more issues in an unorganized way with quantity and variety, more use scenarios and functions with novelty, more behaviors and conflicts identified with quality, and depth-first exploration with all ideation metrics. Fewer hierarchies in use scenarios lower novelty and fewer links to requirements and issues lower quality of ideas.
The third experiment was to see if problem formulation can predict creative outcome. Models based on one problem were used to predict the creativity of another. Predicted scores were compared to assessments of independent judges. Quality and novelty are predicted more accurately than variety, and quantity. Backward elimination improves model fit, though reduces prediction accuracy.
P-maps provide a theoretical framework for formalizing, tracing, and quantifying conceptual design strategies. Other potential applications are developing a test of problem formulation skill, tracking students' learning of formulation skills in a course, and reproducing other researchers’ observations about designer thinking.
This dissertation proposes the Problem Map (P-maps) ontological framework. P-maps represent designers' problem formulation in terms of six groups of entities (requirement, use scenario, function, artifact, behavior, and issue). Entities have hierarchies within each group and links among groups. Variables extracted from P-maps characterize problem formulation.
Three experiments were conducted. The first experiment was to study the similarities and differences between novice and expert designers. Results show that experts use more abstraction than novices do and novices are more likely to add entities in a specific order. Experts also discover more issues.
The second experiment was to see how problem formulation relates to creativity. Ideation metrics were used to characterize creative outcome. Results include but are not limited to a positive correlation between adding more issues in an unorganized way with quantity and variety, more use scenarios and functions with novelty, more behaviors and conflicts identified with quality, and depth-first exploration with all ideation metrics. Fewer hierarchies in use scenarios lower novelty and fewer links to requirements and issues lower quality of ideas.
The third experiment was to see if problem formulation can predict creative outcome. Models based on one problem were used to predict the creativity of another. Predicted scores were compared to assessments of independent judges. Quality and novelty are predicted more accurately than variety, and quantity. Backward elimination improves model fit, though reduces prediction accuracy.
P-maps provide a theoretical framework for formalizing, tracing, and quantifying conceptual design strategies. Other potential applications are developing a test of problem formulation skill, tracking students' learning of formulation skills in a course, and reproducing other researchers’ observations about designer thinking.
ContributorsDinar, Mahmoud (Author) / Shah, Jami J. (Thesis advisor) / Langley, Pat (Committee member) / Davidson, Joseph K. (Committee member) / Lande, Micah (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Nanoparticle suspensions, popularly termed “nanofluids,” have been extensively investigated for their thermal and radiative properties. Such work has generated great controversy, although it is arguably accepted today that the presence of nanoparticles rarely leads to useful enhancements in either thermal conductivity or convective heat transfer. On the other hand, there are still examples of unanticipated enhancements to some properties, such as the reported specific heat of molten salt-based nanofluids and the critical heat flux. Another largely overlooked example is the apparent effect of nanoparticles on the effective latent heat of vaporization (hfg) of aqueous nanofluids. A previous study focused on molecular dynamics (MD) modeling supplemented with limited experimental data to suggest that hfg increases with increasing nanoparticle concentration.
Here, this research extends that exploratory work in an effort to determine if hfg of aqueous nanofluids can be manipulated, i.e., increased or decreased, by the addition of graphite or silver nanoparticles. Our results to date indicate that hfg can be substantially impacted, by up to ± 30% depending on the type of nanoparticle. Moreover, this dissertation reports further experiments with changing surface area based on volume fraction (0.005% to 2%) and various nanoparticle sizes to investigate the mechanisms for hfg modification in aqueous graphite and silver nanofluids. This research also investigates thermophysical properties, i.e., density and surface tension in aqueous nanofluids to support the experimental results of hfg based on the Clausius - Clapeyron equation. This theoretical investigation agrees well with the experimental results. Furthermore, this research investigates the hfg change of aqueous nanofluids with nanoscale studies in terms of melting of silver nanoparticles and hydrophobic interactions of graphite nanofluid. As a result, the entropy change due to those mechanisms could be a main cause of the changes of hfg in silver and graphite nanofluids.
Finally, applying the latent heat results of graphite and silver nanofluids to an actual solar thermal system to identify enhanced performance with a Rankine cycle is suggested to show that the tunable latent heat of vaporization in nanofluilds could be beneficial for real-world solar thermal applications with improved efficiency.
Here, this research extends that exploratory work in an effort to determine if hfg of aqueous nanofluids can be manipulated, i.e., increased or decreased, by the addition of graphite or silver nanoparticles. Our results to date indicate that hfg can be substantially impacted, by up to ± 30% depending on the type of nanoparticle. Moreover, this dissertation reports further experiments with changing surface area based on volume fraction (0.005% to 2%) and various nanoparticle sizes to investigate the mechanisms for hfg modification in aqueous graphite and silver nanofluids. This research also investigates thermophysical properties, i.e., density and surface tension in aqueous nanofluids to support the experimental results of hfg based on the Clausius - Clapeyron equation. This theoretical investigation agrees well with the experimental results. Furthermore, this research investigates the hfg change of aqueous nanofluids with nanoscale studies in terms of melting of silver nanoparticles and hydrophobic interactions of graphite nanofluid. As a result, the entropy change due to those mechanisms could be a main cause of the changes of hfg in silver and graphite nanofluids.
Finally, applying the latent heat results of graphite and silver nanofluids to an actual solar thermal system to identify enhanced performance with a Rankine cycle is suggested to show that the tunable latent heat of vaporization in nanofluilds could be beneficial for real-world solar thermal applications with improved efficiency.
ContributorsLee, Soochan (Author) / Phelan, Patrick E (Thesis advisor) / Wu, Carole-Jean (Thesis advisor) / Wang, Robert (Committee member) / Wang, Liping (Committee member) / Taylor, Robert A. (Committee member) / Prasher, Ravi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Hydrogel polymers have been the subject of many studies, due to their fascinating ability to alternate between being hydrophilic and hydrophobic, upon the application of appropriate stimuli. In particular, thermo-responsive hydrogels such as N-Isopropylacrylamide (NIPAM), which possess a unique lower critical solution temperature (LCST) of 32°C, have been leveraged for membrane-based processes such as using NIPAM as a draw agent for forward osmosis (FO) desalination. The low LCST temperature of NIPAM ensures that fresh water can be recovered, at a modest energy cost as compared to other thermally based desalination processes which require water recovery at higher temperatures. This work studies by experimentation, key process parameters involved in desalination by FO using NIPAM and a copolymer of NIPAM and Sodium Acrylate (NIPAM-SA). It encompasses synthesis of the hydrogels, development of experiments to effectively characterize synthesized products, and the measuring of FO performance for the individual hydrogels. FO performance was measured using single layers of NIPAM and NIPAM-SA respectively. The values of permeation flux obtained were compared to relevant published literature and it was found to be within reasonable range. Furthermore, a conceptual design for future large-scale implementation of this technology is proposed. It is proposed that perhaps more effort should focus on physical processes that have the ability to increase the low permeation flux of hydrogel driven FO desalination systems, rather than development of novel classes of hydrogels
ContributorsAbdullahi, Adnan None (Author) / Phelan, Patrick (Thesis advisor) / Wang, Robert (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2019
Description
Thermodynamic development and balance of plant study is completed for a 30 MW solar thermochemical water splitting process that generates hydrogen gas and electric power. The generalized thermodynamic model includes 23 components and 45 states. Quasi-steady state simulations are completed for design point system sizing, annual performance analysis and sensitivity analysis. Detailed consideration is given to water splitting reaction kinetics with governing equations generalized for use with any redox-active metal oxide material. Specific results for Ceria illustrate particle reduction in two solar receivers for target oxygen partial pressure of 10 Pa and particle temperature of 1773 K at a design point DNI of 900 W/m2. Sizes of the recuperator, steam generator and hydrogen separator are calculated at the design point DNI to achieve 100,000 kg of hydrogen production per day from the plant. The total system efficiency of 39.52% is comprised of 50.7% hydrogen fraction and 19.62% electrical fraction. Total plant capital costs and operating costs are estimated to equate a hydrogen production cost of $4.40 per kg for a 25-year plant life. Sensitivity analysis explores the effect of environmental parameters and design parameters on system performance and cost. Improving recuperator effectiveness from 0.7 to 0.8 is a high-value design modification resulting in a 12.1% decrease in hydrogen cost for a modest 2.0% increase in plant $2.85M. At the same time, system efficiency is relatively inelastic to recuperator effectiveness because 81% of excess heat is recovered from the system for electricity production 39 MWh/day and revenue is $0.04 per kWh. Increasing water inlet pressure up to 20 bar reduces the size and cost of super heaters but further pressure rises increasing pump at a rate that outweighs super heater cost savings.
ContributorsBudama, Vishnu Kumar (Author) / Johnson, Nathan (Thesis advisor) / Stechel, Ellen (Committee member) / Rykaczewski, Konrad (Committee member) / Phelan, Patrick (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2018
Description
The objective of this dissertation is to study the use of metamaterials as narrow-band and broadband selective absorbers for opto-thermal and solar thermal energy conversion. Narrow-band selective absorbers have applications such as plasmonic sensing and cancer treatment, while one of the main applications of selective metamaterials with broadband absorption is efficiently converting solar energy into heat as solar absorbers.
This dissertation first discusses the use of gold nanowires as narrow-band selective metamaterial absorbers. An investigation into plasmonic localized heating indicated that film-coupled gold nanoparticles exhibit tunable selective absorption based on the size of the nanoparticles. By using anodized aluminum oxide templates, aluminum nanodisc narrow-band absorbers were fabricated. A metrology instrument to measure the reflectance and transmittance of micro-scale samples was also developed and used to measure the reflectance of the aluminum nanodisc absorbers (220 µm diameter area). Tuning of the resonance wavelengths of these absorbers can be achieved through changing their geometry. Broadband absorption can be achieved by using a combination of geometries for these metamaterials which would facilitate their use as solar absorbers.
Recently, solar energy harvesting has become a topic of considerable research investigation due to it being an environmentally conscious alternative to fossil fuels. The next section discusses the steady-state temperature measurement of a lab-scale multilayer solar absorber, named metafilm. A lab-scale experimental setup is developed to characterize the solar thermal performance of selective solar absorbers. Under a concentration factor of 20.3 suns, a steady-state temperature of ~500 degrees Celsius was achieved for the metafilm compared to 375 degrees Celsius for a commercial black absorber under the same conditions. Thermal durability testing showed that the metafilm could withstand up to 700 degrees Celsius in vacuum conditions and up to 400 degrees Celsius in atmospheric conditions with little degradation of its optical and radiative properties. Moreover, cost analysis of the metafilm found it to cost significantly less ($2.22 per square meter) than commercial solar coatings ($5.41-100 per square meter).
Finally, this dissertation concludes with recommendations for further studies like using these selective metamaterials and metafilms as absorbers and emitters and using the aluminum nanodiscs on glass as selective filters for photovoltaic cells to enhance solar thermophotovoltaic energy conversion.
This dissertation first discusses the use of gold nanowires as narrow-band selective metamaterial absorbers. An investigation into plasmonic localized heating indicated that film-coupled gold nanoparticles exhibit tunable selective absorption based on the size of the nanoparticles. By using anodized aluminum oxide templates, aluminum nanodisc narrow-band absorbers were fabricated. A metrology instrument to measure the reflectance and transmittance of micro-scale samples was also developed and used to measure the reflectance of the aluminum nanodisc absorbers (220 µm diameter area). Tuning of the resonance wavelengths of these absorbers can be achieved through changing their geometry. Broadband absorption can be achieved by using a combination of geometries for these metamaterials which would facilitate their use as solar absorbers.
Recently, solar energy harvesting has become a topic of considerable research investigation due to it being an environmentally conscious alternative to fossil fuels. The next section discusses the steady-state temperature measurement of a lab-scale multilayer solar absorber, named metafilm. A lab-scale experimental setup is developed to characterize the solar thermal performance of selective solar absorbers. Under a concentration factor of 20.3 suns, a steady-state temperature of ~500 degrees Celsius was achieved for the metafilm compared to 375 degrees Celsius for a commercial black absorber under the same conditions. Thermal durability testing showed that the metafilm could withstand up to 700 degrees Celsius in vacuum conditions and up to 400 degrees Celsius in atmospheric conditions with little degradation of its optical and radiative properties. Moreover, cost analysis of the metafilm found it to cost significantly less ($2.22 per square meter) than commercial solar coatings ($5.41-100 per square meter).
Finally, this dissertation concludes with recommendations for further studies like using these selective metamaterials and metafilms as absorbers and emitters and using the aluminum nanodiscs on glass as selective filters for photovoltaic cells to enhance solar thermophotovoltaic energy conversion.
ContributorsAlshehri, Hassan (Author) / Wang, Liping (Thesis advisor) / Phelan, Patrick (Committee member) / Rykaczewski, Konrad (Committee member) / Wang, Robert (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2018
Description
When air is supplied to a conditioned space, the temperature and humidity of the air often contribute to the comfort and health of the occupants within the space. However, the vapor compression system, which is the standard air conditioning configuration, requires air to reach the dew point for dehumidification to occur, which can decrease system efficiency and longevity in low temperature applications.
To improve performance, some systems dehumidify the air before cooling. One common dehumidifier is the desiccant wheel, in which solid desiccant absorbs moisture out of the air while rotating through circular housing. This system improves performance, especially when the desiccant is regenerated with waste or solar heat; however, the heat of regeneration is very large, as the water absorbed during dehumidification must be evaporated. N-isopropylacrylamide (NIPAAm), a sorbent that oozes water when raised above a certain temperature, could potentially replace traditional desiccants in dehumidifiers. The heat of regeneration for NIPAAm consists of some sensible heat to bring the sorbent to the regeneration temperature, plus some latent heat to offset any liquid water that is evaporated as it is exuded from the NIPAAm. This means the NIPAAm regeneration heat has the potential to be much lower than that of a traditional desiccant.
Models were created for a standard vapor compression air conditioning system, two desiccant systems, and two theoretical NIPAAm systems. All components were modeled for simplified steady state operation. For a moderate percent of water evaporated during regeneration, it was found that the NIPAAm systems perform better than standard vapor compression. When compared to the desiccant systems, the NIPAAm systems performed better at almost all percent evaporation values. The regeneration heat was modeled as if supplied by an electric heater. If a cheaper heat source were utilized, the case for NIPAAm would be even stronger.
Future work on NIPAAm dehumidification should focus on lowering the percent evaporation from the 67% value found in literature. Additionally, the NIPAAm cannot exceed the lower critical solution temperature during dehumidification, indicating that a NIPAAm dehumidification system should be carefully designed such that the sorbent temperature is kept sufficiently low during dehumidification.
To improve performance, some systems dehumidify the air before cooling. One common dehumidifier is the desiccant wheel, in which solid desiccant absorbs moisture out of the air while rotating through circular housing. This system improves performance, especially when the desiccant is regenerated with waste or solar heat; however, the heat of regeneration is very large, as the water absorbed during dehumidification must be evaporated. N-isopropylacrylamide (NIPAAm), a sorbent that oozes water when raised above a certain temperature, could potentially replace traditional desiccants in dehumidifiers. The heat of regeneration for NIPAAm consists of some sensible heat to bring the sorbent to the regeneration temperature, plus some latent heat to offset any liquid water that is evaporated as it is exuded from the NIPAAm. This means the NIPAAm regeneration heat has the potential to be much lower than that of a traditional desiccant.
Models were created for a standard vapor compression air conditioning system, two desiccant systems, and two theoretical NIPAAm systems. All components were modeled for simplified steady state operation. For a moderate percent of water evaporated during regeneration, it was found that the NIPAAm systems perform better than standard vapor compression. When compared to the desiccant systems, the NIPAAm systems performed better at almost all percent evaporation values. The regeneration heat was modeled as if supplied by an electric heater. If a cheaper heat source were utilized, the case for NIPAAm would be even stronger.
Future work on NIPAAm dehumidification should focus on lowering the percent evaporation from the 67% value found in literature. Additionally, the NIPAAm cannot exceed the lower critical solution temperature during dehumidification, indicating that a NIPAAm dehumidification system should be carefully designed such that the sorbent temperature is kept sufficiently low during dehumidification.
ContributorsKocher, Jordan Daniel (Author) / Wang, Robert (Thesis advisor) / Phelan, Patrick (Committee member) / Parrish, Kristen (Committee member) / Arizona State University (Publisher)
Created2019
Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Aging-related damage and failure in structures, such as fatigue cracking, corrosion, and delamination, are critical for structural integrity. Most engineering structures have embedded defects such as voids, cracks, inclusions from manufacturing. The properties and locations of embedded defects are generally unknown and hard to detect in complex engineering structures. Therefore, early detection of damage is beneficial for prognosis and risk management of aging infrastructure system.
Non-destructive testing (NDT) and structural health monitoring (SHM) are widely used for this purpose. Different types of NDT techniques have been proposed for the damage detection, such as optical image, ultrasound wave, thermography, eddy current, and microwave. The focus in this study is on the wave-based detection method, which is grouped into two major categories: feature-based damage detection and model-assisted damage detection. Both damage detection approaches have their own pros and cons. Feature-based damage detection is usually very fast and doesn’t involve in the solution of the physical model. The key idea is the dimension reduction of signals to achieve efficient damage detection. The disadvantage is that the loss of information due to the feature extraction can induce significant uncertainties and reduces the resolution. The resolution of the feature-based approach highly depends on the sensing path density. Model-assisted damage detection is on the opposite side. Model-assisted damage detection has the ability for high resolution imaging with limited number of sensing paths since the entire signal histories are used for damage identification. Model-based methods are time-consuming due to the requirement for the inverse wave propagation solution, which is especially true for the large 3D structures.
The motivation of the proposed method is to develop efficient and accurate model-based damage imaging technique with limited data. The special focus is on the efficiency of the damage imaging algorithm as it is the major bottleneck of the model-assisted approach. The computational efficiency is achieved by two complimentary components. First, a fast forward wave propagation solver is developed, which is verified with the classical Finite Element(FEM) solution and the speed is 10-20 times faster. Next, efficient inverse wave propagation algorithms is proposed. Classical gradient-based optimization algorithms usually require finite difference method for gradient calculation, which is prohibitively expensive for large degree of freedoms. An adjoint method-based optimization algorithms is proposed, which avoids the repetitive finite difference calculations for every imaging variables. Thus, superior computational efficiency can be achieved by combining these two methods together for the damage imaging. A coupled Piezoelectric (PZT) damage imaging model is proposed to include the interaction between PZT and host structure. Following the formulation of the framework, experimental validation is performed on isotropic and anisotropic material with defects such as cracks, delamination, and voids. The results show that the proposed method can detect and reconstruct multiple damage simultaneously and efficiently, which is promising to be applied to complex large-scale engineering structures.
Non-destructive testing (NDT) and structural health monitoring (SHM) are widely used for this purpose. Different types of NDT techniques have been proposed for the damage detection, such as optical image, ultrasound wave, thermography, eddy current, and microwave. The focus in this study is on the wave-based detection method, which is grouped into two major categories: feature-based damage detection and model-assisted damage detection. Both damage detection approaches have their own pros and cons. Feature-based damage detection is usually very fast and doesn’t involve in the solution of the physical model. The key idea is the dimension reduction of signals to achieve efficient damage detection. The disadvantage is that the loss of information due to the feature extraction can induce significant uncertainties and reduces the resolution. The resolution of the feature-based approach highly depends on the sensing path density. Model-assisted damage detection is on the opposite side. Model-assisted damage detection has the ability for high resolution imaging with limited number of sensing paths since the entire signal histories are used for damage identification. Model-based methods are time-consuming due to the requirement for the inverse wave propagation solution, which is especially true for the large 3D structures.
The motivation of the proposed method is to develop efficient and accurate model-based damage imaging technique with limited data. The special focus is on the efficiency of the damage imaging algorithm as it is the major bottleneck of the model-assisted approach. The computational efficiency is achieved by two complimentary components. First, a fast forward wave propagation solver is developed, which is verified with the classical Finite Element(FEM) solution and the speed is 10-20 times faster. Next, efficient inverse wave propagation algorithms is proposed. Classical gradient-based optimization algorithms usually require finite difference method for gradient calculation, which is prohibitively expensive for large degree of freedoms. An adjoint method-based optimization algorithms is proposed, which avoids the repetitive finite difference calculations for every imaging variables. Thus, superior computational efficiency can be achieved by combining these two methods together for the damage imaging. A coupled Piezoelectric (PZT) damage imaging model is proposed to include the interaction between PZT and host structure. Following the formulation of the framework, experimental validation is performed on isotropic and anisotropic material with defects such as cracks, delamination, and voids. The results show that the proposed method can detect and reconstruct multiple damage simultaneously and efficiently, which is promising to be applied to complex large-scale engineering structures.
ContributorsChang, Qinan (Author) / Liu, Yongming (Thesis advisor) / Mignolet, Marc (Committee member) / Chattopadhyay, Aditi (Committee member) / Yan, Hao (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2019
Description
This thesis evaluates the viability of an original design for a cost-effective wheel-mounted dynamometer for road vehicles. The goal is to show whether or not a device that generates torque and horsepower curves by processing accelerometer data collected at the edge of a wheel can yield results that are comparable to results obtained using a conventional chassis dynamometer. Torque curves were generated via the experimental method under a variety of circumstances and also obtained professionally by a precision engine testing company. Metrics were created to measure the precision of the experimental device's ability to consistently generate torque curves and also to compare the similarity of these curves to the professionally obtained torque curves. The results revealed that although the test device does not quite provide the same level of precision as the professional chassis dynamometer, it does create torque curves that closely resemble the chassis dynamometer torque curves and exhibit a consistency between trials comparable to the professional results, even on rough road surfaces. The results suggest that the test device provides enough accuracy and precision to satisfy the needs of most consumers interested in measuring their vehicle's engine performance but probably lacks the level of accuracy and precision needed to appeal to professionals.
ContributorsKing, Michael (Author) / Ren, Yi (Thesis director) / Spanias, Andreas (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05