A novel concept for integration of flame-assisted fuel cells (FFC) with a gas turbine is analyzed in this paper. Six different fuels (CH4, C3H8, JP-4, JP-5, JP-10(L), and H2) are investigated for the analytical model of the FFC integrated gas turbine hybrid system. As equivalence ratio increases, the efficiency of the hybrid system increases initially then decreases because the decreasing flow rate of air begins to outweigh the increasing hydrogen concentration. This occurs at an equivalence ratio of 2 for CH4. The thermodynamic cycle is analyzed using a temperature entropy diagram and a pressure volume diagram. These thermodynamic diagrams show as equivalence ratio increases, the power generated by the turbine in the hybrid setup decreases. Thermodynamic analysis was performed to verify that energy is conserved and the total chemical energy going into the system was equal to the heat rejected by the system plus the power generated by the system. Of the six fuels, the hybrid system performs best with H2 as the fuel. The electrical efficiency with H2 is predicted to be 27%, CH4 is 24%, C3H8 is 22%, JP-4 is 21%, JP-5 is 20%, and JP-10(L) is 20%. When H2 fuel is used, the overall integrated system is predicted to be 24.5% more efficient than the standard gas turbine system. The integrated system is predicted to be 23.0% more efficient with CH4, 21.9% more efficient with C3H8, 22.7% more efficient with JP-4, 21.3% more efficient with JP-5, and 20.8% more efficient with JP-10(L). The sensitivity of the model is investigated using various fuel utilizations. When CH4 fuel is used, the integrated system is predicted to be 22.7% more efficient with a fuel utilization efficiency of 90% compared to that of 30%.
Startups in the paper manufacturing industry are few and far between. Agrix paper takes a step towards innovating the traditional mass-scale paper making process and introduces non-wood fiber sourcing into the papermaking space. Using a hemp fiber base, Agrix Paper hopes to develop a new paper manufacturing process that derives high-quality paper sourced from hemp and agriculture waste. Agrix Paper will reinvent the papermaking process for a more green and sustainable future.
Baking is a popular past-time among Generation Z, and ‘bakeries’ are an equally popular intention. Baked by Barrett is a charity-oriented bake-sale platform for Generation Z members who are passionate about baking, and would like to sell their goods within the Tempe, Arizona college ecosystem. Baked by Barrett facilitates the collection, review and sale of home baked goods through various means on a weekly cadence. This will include, while not limited to, hosting tabling and social events throughout the academic year. This user-led platform will share the proceeds towards bakers, local charities of choice as well as maintaining a percentage internally to ensure efficient operations. Because businesses for profit are a conflict of interest for ASU, the organization will work to promote students and charity along with the learning for business and entrepreneurial ventures. Instead of generating profits, Baked by Barrett will focus on sustaining itself while the rest of the revenue will go to charity. This will help the organization avoid conflicts of interest with asu allowing it to use campus space to sell. Marketing will, initially, be based on word-of-mouth, with supporting tools including a dynamic website, flyers and partnerships around local newsletters. Rotations of charities and menu items will be used to add incentives for students and passersby to buy from Baked by Barrett. In order to promote the organization, there will be a website, flyers and even contact information through the Barrett digest to market the platform in the weekly newsletter.
This paper analyzes responses to deviated Trolley Problem scenarios [5] in a simulated driving environment and still images from MIT’s moral machine website [8] to better understand how humans respond to various crashes. Also included is participants driving habits and personal values, however the bulk of that analysis is not included here. The results of the simulation prove that for the most part in driving scenarios, people would rather sacrifice themselves over people outside of the vehicle. The moral machine scenarios prove that self-sacrifice changes as the trend to harm one’s own vehicle was not so strong when passengers were introduced. Further defending this idea is the importance placed on Family Security over any other value.
Suggestions for implementing ethics into autonomous vehicle crashes stem from the results of this experiment but are dependent on more research and greater sample sizes. Once enough data is collected and analyzed, a moral baseline for human’s moral domain may be agreed upon, quantified, and turned into hard rules governing how self-driving cars should act in different scenarios. With these hard rules as boundary conditions, artificial intelligence should provide training and incremental learning for scenarios which cannot be determined by the rules. Finally, the neural networks which make decisions in artificial intelligence must move from their current “black box” state to something more traceable. This will allow researchers to understand why an autonomous vehicle made a certain decision and allow tweaks as needed.
To achieve this goal, a model of a swarm performing a collective transport task in a bounded domain featuring convex obstacles was simulated in MATLAB/ Simulink®. The closed-loop dynamic equations of this model were linearized about an equilibrium state with angular acceleration and linear acceleration set to zero. The simulation was run over 30 times to confirm system ability to successfully transport the payload to a goal point without colliding with obstacles and determine ideal operating conditions by testing various orientations of objects in the bounded domain. An additional purely MATLAB simulation was run to identify local minima of the Hessian of the navigation-like potential function. By calculating this Hessian periodically throughout the system’s progress and determining the signs of its eigenvalues, a system could check whether it is trapped in a local minimum, and potentially dislodge itself through implementation of a stochastic term in the robot controllers. The eigenvalues of the Hessian calculated in this research suggested the model local minima were degenerate, indicating an error in the mathematical model for this system, which likely incurred during linearization of this highly nonlinear system.