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The focus of this research lies on fundamental research to provide guidelines for the design of new nanocatalyst toward improvement of the performance of proton exchange membrane fuel cells (PEMFCs). To achieve this overarching goal, several specific steps were taken with aims to: (1) provide guidelines for the design of new catalysts; (2) promote nanocatalyst applications towards alternative energy applications; and (3) integrate advanced instrumentation into nanocharacterization and fuel cell (FC) electrochemical behavior. In tandem with these goals, the cathode catalysts were extensively refined to improve the performance of PEMFCs and minimize noble metal usage. In this study, the major accomplishment was producing aligned carbon nanotubes (ACNTs), which were then modified by platinum (Pt) nanoparticles via a post-functionalization colloidal chemistry approach. The Pt-ACNTs demonstrated improved cathodic catalycity, by building better device endurance and decreased Pt loading. It was also determined that surface mechanical properties, such as elastic modulus and hardness were increased. Collectively, these enhancements provided an improved FC device. The electrochemical analyses indicated that the power density of the PEMFCs was increased to 900 mW/cm2 and current density to 3000 mA/cm2, respectively. The Pt loading was controlled at lower than 0.2 mg/cm2 to decrease the manufacturing expenses.

Recycled polylactic acid (PLAr) was reinforced with treated nanocellulosic hemp fibers for biocomposite fabrication. Cellulosic fibers were extracted from hemp fibers chemically and treated enzymatically. Treated nanocellulosic fibers (NCF) were analyzed by Fourier-transform infrared spectroscopy, X-ray diffraction, and scanning electron microscopy. Biocomposite fabrication was done with PLAr and three concentrations of treated NCF (0.1%, 0.25%, and 1% (v/v)) and then studied for thermal stability and mechanical properties. Increased thermal stability was observed with increasing NCF concentrations. The highest value for Young’s modulus was for PLAr + 0.25% (v/v) NCF (250.28 ± 5.47 MPa), which was significantly increased compared to PLAr (p = 0.022). There was a significant decrease in the tensile stress at break point for PLAr + 0.25% (v/v) NCF and PLAr + 1% (v/v) NCF as compared to control (p = 0.006 and 0.002, respectively). No significant difference was observed between treatments for tensile stress at yield.

Oil shale is a kind of potential alternative energy source for petroleum and has attracted the attention of energy researchers all over the world. Borehole hydraulic mining has more prominent advantages than both conventional open-pit mining and underground mining. It is very important to attempt to use the borehole hydraulic mining method to exploit underground oil shale. The nozzle is the key component of borehole hydraulic mining and reasonable mining parameters are also crucial in exploiting underground oil shale efficiently. The straight cone nozzle and the oil shale of Huadian area will be taken as the research objects. The self-developed, multifunctional, experimental device can test both the jet’s performance as well as the breaking of oil shale by the high-pressure water jet using the straight cone nozzle and varying structural parameters. Comprehensive analysis of the results of an orthogonal experimental design, including range analysis and variance analysis, demonstrate the optimal structural parameters of a straight cone nozzle as follows: the outlet diameter is 4 mm, the length to diameter ratio is 2.5, and the contraction angle is 60°. In addition, in order to maximize the efficiency of borehole hydraulic mining for Huadian oil shale, the non-submerged jet should be placed parallel to the oil shale bedding. These results can provide scientific and valuable references for borehole hydraulic mining of oil shale.

Nuclear power plants in the United States are increasingly challenged to compete in wholesale electricity markets due to the low electricity costs and increasingly dynamic grid conditions from competing generation sources. An alternative market for nuclear power is industrial facilities that can use the thermal and/or electrical power generated by a nuclear power plant to offset the economic losses incurred by electricity market challenges. A generic pressurized water reactor (PWR) simulator was used to show the results of a basic design for a generic thermal power extraction system and tests were run using a set of procedures to show what happens when a nuclear power plant transitions from full electrical power dispatch to 15% and 50% thermal power dispatch. This type of operation leads to losses in turbine performance efficiency due to the deviation from the design operating point, but because the thermal power is also used by the industry load without conversion losses, the combined thermal efficiency of the PWR increases. For the 15% case, the thermal efficiency increased from 32% to 41.9%, while for the 50% case, the efficiency increased up to 60.1%. In addition, for 50% thermal power dispatch, the power dissipated by the condenser decreased from approximately 2000 to approximately 1300 MW (thermal), indicating a substantially diminished impact on the environment in terms of releasing heat into the cooling water reservoir.

In this paper, recent achievements in the application of the lattice Boltzmann method (LBM) to complex fluid flows are reported. More specifically, we focus on flows through reactive porous media, such as the flow through the substrate of a selective catalytic reactor (SCR) for the reduction of gaseous pollutants in the automotive field; pulsed-flow analysis through heterogeneous catalyst architectures; and transport and electro-chemical phenomena in microbial fuel cells (MFC) for novel waste-to-energy applications. To the authors’ knowledge, this is the first known application of LBM modeling to the study of MFCs, which represents by itself a highly innovative and challenging research area. The results discussed here essentially confirm the capabilities of the LBM approach as a flexible and accurate computational tool for the simulation of complex multi-physics phenomena of scientific and technological interest, across physical scales.

Fire hazard during ship transportation of certain modern solid fuels is identified. A particular mechanism which may lead to catastrophic ship fire is discussed. A mathematical model predicting time to such fully developed fire (flashover time) I s proposed. An analytical solution is obtained for the developed model. An important part of this solution is a closed form analytical description of the smoke filling dynamics in a closed compartment. It is demonstrated that flashover time depends on a number of parameters. The relative importance of these parameters is discussed. Particular significance is attributed to fuel soot propensity (fuel soot yield) which is an intrinsic fuel property. This parameter controls the intensity of radiative heat exchange in the compartment, and its influence on flashover time is of paramount importance. It is suggested that fuels are ranked with respect to this parameter in order to describe their relative fire hazards. This ranking should be implemented into the regulatory framework governing fuel transportation by ships.

One direction in optimizing wind farm production is reducing wake interactions from upstream turbines. This can be done by optimizing turbine layout as well as optimizing turbine yaw and pitch angles. In particular, wake steering by optimizing yaw angles of wind turbines in farms has received significant attention in recent years. One of the challenges in yaw optimization is developing fast optimization algorithms which can find good solutions in real-time. In this work, we developed a random search algorithm to optimize yaw angles. Optimization was performed on a layout of 39 turbines in a 2 km by 2 km domain. Algorithm specific parameters were tuned for highest solution quality and lowest computational cost. Testing showed that this algorithm can find near-optimal (<1% of best known solutions) solutions consistently over multiple runs, and that quality solutions can be found under 200 iterations. Empirical results show that as wind farm density increases, the potential for yaw optimization increases significantly, and that quality solutions are likely to be plentiful and not unique.