Application of Steepest-Entropy-Ascent Quantum Thermodynamics to Predicting Heat and Mass Diffusion From the Atomistic Up to the Macroscopic Level

Conventional first principle approaches for studying non-equilibrium or far-from-equilibrium processes all depend on the mechanics of individual particles or quantum states and as a result, require too many details of the mechanical features of the system to easily or even practically arrive at the value of a macroscopic property. In contrast, thermodynamics, which has been extremely successful in the stable equilibrium realm, provides an approach for determining a macroscopic property without going into the mechanical details. Nonetheless, such a phenomenological approach is not generally applicable to a non-equilibrium process except in the near-equilibrium realm and under the limiting local equilibrium and continuum assumptions, both of which prevent its application across all scales. To address these drawbacks, steepest-entropy-ascent quantum thermodynamics (SEAQT) can be used. It provides an ensemble-based, thermodynamics, first principles approach applicable to the entire non-equilibrium realm even that far-from-equilibrium and does so with a single kinematics and dynamics able to cross all temporal and spatial scales. Based on prior developments by the authors, this paper applies SEAQT to the study of mass and heat diffusion. Specifically, the study focuses on the thermodynamic features of far-from-equilibrium state evolution. Two kinds of size effects on the evolution trajectory, i.e., concentration and volume effects, are discussed.

Application of Advanced Model of Zr-Based Cladding Oxidation in Steam-Oxygen-Nitrogen Gas Mixtures to Separate Effects Tests and Integral Experiments

During postulated design-basis or beyond-design-basis accident at nuclear power plant with PWR or BWR, the high temperature oxidation of Zr-based fuel claddings in H2O-O2-N2 gas atmosphere could take place. Recent experimental observations showed that the oxidation of those claddings in the air (or, more generally, in oxygen-nitrogen and steam-nitrogen mixtures) behaves in much more aggressive way (linear or enhanced parabolic kinetics) compared to oxidation in pure steam (standard parabolic kinetics). This is why an advanced model of Zr-based cladding oxidation was developed. For calculations of cladding oxidation in oxygen-nitrogen and steam-nitrogen mixtures, the effective oxygen diffusion coefficient in ZrO2+ZrN layer formed in cladding is used. The diffusion coefficient enhancement factor depends on ZrN content in ZrO2+ZrN layer. A numerical scheme was realized to determine ZrO2+ZrN/α-Zr(O) and α-Zr(O)/β-Zr layers boundaries relocation and layers transformations in claddings. The model was implemented to the SOCRAT best estimate computer modeling code. The SOCRAT code with advanced model of oxidation was successfully used for calculations of separate effects tests and air ingress integral experiments QUENCH-10, QUENCH-16 and PARAMETER-SF4.

A Comparative Study of Hydrogen Storage and Hydrocarbon Fuel Processing for Automotive Fuel Cells

In recent years, there has been increased interest in fuel cells as a promising energy storage technology. The environmental impacts due to the extensive fossil fuel consumption is becoming increasingly important as greenhouse gas (GHG) levels in the atmosphere continue to rise rapidly. Furthermore, fuel cell efficiencies are not limited by the Carnot limit, a major thermodynamic limit for power plants and internal combustion engines. Therefore, hydrogen fuel cells could provide a long-term solution to the automotive industry, in its search for alternate propulsion systems. Two most important methods for hydrogen delivery to fuel cells used for vehicle propulsion were evaluated in this study, which are fuel processing and hydrogen storage. Moreover, the average fuel cost and the greenhouse gas emission for hydrogen fuel cell (H2 FCV) and gasoline fuel cell (GFCV) vehicles are compared to that of a regular gasoline vehicle based on the Argonne National Lab’s GREET model. The results show that the average fuel cost per 100 miles for a H2 FCV can be up to 57% lower than that of regular gasoline vehicles. Moreover, the obtained results confirm that the well to wheel greenhouse gas emission of both H2 FCV and GFCV is significantly less than that of regular gasoline vehicles. Furthermore, the investment return period for hydrogen storage techniques are compared to fuel processing methods. A qualitative safety and infrastructure dependency comparison of hydrogen storage and fuel processing methods is also presented.

The Simulation of Natural Ventilation of Buildings With Different Location of Windows/Openings

Ventilation is a process of changing air in an enclosed space. Air should continuously be withdrawn and replaced by fresh air from a clean external source to maintain internal good air quality, which may referred to air quality within and around the building structures. In natural ventilation the air flow is due through cracks in the building envelope or purposely installed openings. Its can save significant amount of fossil fuel based energy by reducing the needs for mechanical ventilation and air conditioning. Numerical predictions of air velocities and the flow patterns inside the building are determined. To achieve optimum efficiency of natural ventilation, the building design should start from the climatic conditions and orography of the construction to ensure the building permeability to the outside airflow to absorb heat from indoors to reduce temperatures. Effective ventilation in a building will affects the occupant health and productivity. In this work, computational simulation is performed on a real-sized box-room with dimensions 5 m × 5 m × 5 m. Single-sided ventilation is considered whereby openings are located only on the same wall. Two opening of the total area 4 m2 are differently arranged, resulting in 16 configurations to be investigated. A logarithmic wind profile upwind of the building is employed. A commercial Computational Fluid Dynamics (CFD) software package CFD-ACE of ESI group is used. A Reynolds Average Navier Stokes (RANS) turbulence model & LES turbulence model are used to predict the air’s flow rate and air flow pattern. The governing equations for large eddy motion were obtained by filtering the Navier-Stokes and continuity equations. The computational domain was constructed had a height of 4H, width of 9H and length of 13H (H=5m), sufficiently large to avoid disturbance of air flow around the building. From the overall results, the lowest and the highest ventilation rates were obtained with windward opening and leeward opening respectively. The location and arrangement of opening affects ventilation and air flow pattern.

Performance Estimation of Direct Methanol Fuel Cell Using Artificial Neural Network

A direct methanol fuel cell can convert chemical energy in the form of a liquid fuel into electrical energy to power devices, while simultaneously operating at low temperatures and producing virtually no greenhouse gases. Since the direct methanol fuel cell performance characteristics are inherently nonlinear and complex, it can be postulated that artificial neural networks represent a marked improvement in performance prediction capabilities. Artificial neural networks have long been used as a tool in predictive modeling. In this work, an artificial neural network is employed to predict the performance of a direct methanol fuel cell under various operating conditions. This work on the experimental analysis of a uniquely designed fuel cell and the computational modeling of a unique algorithm has not been found in prior literature outside of the authors and their affiliations. The fuel cell input variables for the performance analysis consist not only of the methanol concentration, fuel cell temperature, and current density, but also the number of cells and anode flow rate. The addition of the two typically unconventional variables allows for a more distinctive model when compared to prior neural network models. The key performance indicator of our neural network model is the cell voltage, which is an average voltage across the stack and ranges from 0 to 0:8V. Experimental studies were carried out using DMFC stacks custom-fabricated, with a membrane electrode assembly consisting of an additional unique liquid barrier layer to minimize water loss through the cathode side to the atmosphere. To determine the best fit of the model to the experimental cell voltage data, the model is trained using two different second order training algorithms: OWO-Newton and Levenberg-Marquardt (LM). The OWO-Newton algorithm has a topology that is slightly different from the topology of the LM algorithm by the employment of bypass weights. It can be concluded that the application of artificial neural networks can rapidly construct a predictive model of the cell voltage for a wide range of operating conditions with an accuracy of 10−3 to 10−4. The results were comparable with existing literature. The added dimensionality of the number of cells provided insight into scalability where the coefficient of the determination of the results for the two multi-cell stacks using LM algorithm were up to 0:9998. The model was also evaluated with empirical data of a single-cell stack.

Energy Harvesting Using Galvanically Synthesized Piezoelectric ZnO Nanorods on Flexible Polymer Film

This paper reports advancement in bringing flexible piezoelectric nanogenerators (NGs) closer to being realized in a commercial market. We have adopted a method to synthesize piezoelectric ZnO nanorods (NRs) on any electrically conductive surface without a seed layer or a specially selected substrate with matching lattice spacing. By contacting a metal with a dissimilar electro-negativity, a galvanic cell is created in the electrolyte growth medium. We have demonstrated the performance of the as grown NRs on a thin NG using common PET film. The device produced voltages in excess of three times higher than a parallel fabricated reference sample under bending loads.

SUNTRACKER

A SUNTRACKER (illustrated in figure1), is a Concentrating Solar Power (CSP) unit, in the category of solar dish engines. The novel solar dish engine module (shown in figure 2) is designed to provide 10.1kW electric power (measured at the engine output electric power lugs), from a conversion of 21kW solar energy from the solar dish reflective sun light to the high temperature receiver focal point. Total electric power output from the solar dish engine module is attributed to combined cycles, closed brayton cycle (CBC) and a organic rankine cycle (ORC), both of which are hermetically sealed to atmosphere. The CBC engine receives 21kW solar energy from a solar dish, estimated to have 27 square meters (291 square feet) reflective surface area. However, unlike the photovoltaic (PV) units, the SUNTRACKER will provide increased use of available solar energy from sunlight. Concentrated sunlight from the dish will focus on the CBC engine receiver, which in turn heats the working fluid media to as much as 1600F, pending the ratio of solar dish to receiver areas. A specific gas mixture of xenon/helium, with excellent thermodynamic properties is used for the high temperature application. Turbomachinery in the CBC engine has one moving part / assembly (compressor impeller, alternator rotor and turbine rotor), mounted on compliant foil bearings. Reference figure 4 as an example. The engine operates with a compressor impeller stage pressure ratio 1.6, and is recuperated. Electric power, measured at the CBC engine electric power lugs, is 6.4kW. The CBC engine is not new, (a closed Brayton cycle, sealed to atmosphere) [1], [4], [8], [18], [19]. However, the application to extract thermal energy from the sunlight and provide electric power in commercial and residential use is (patented). In addition, to increase the efficiency of solar energy conversion to electric power, waste heat from the CBC engine provides thermal energy to an ORC engine, to generate an additional electrical output of 3.7kW (measured at the output electric power lugs). With use of an ORC system, the size of the radiator (CBC unit) for heat rejection is reduced significantly. Working fluid HFC-RC245fa [10] was selected for the ORC unit, based on the low temperature application. Also, as with the CBC turbomachinery, the ORC rotor assembly has one moving part, comprised of a pump impeller, alternator rotor and turbine rotor. With the two engines combined, total system thermal efficiency is 48% (10.1kW electric power out / 21kW solar energy in). However, power electronics are needed for conversion of high frequency voltage at the engine output electric power leads to 60/50 Hz power, for customer use. Power electronics losses for this machine, debits the power 0.5 kW. Thus total electric power to the customer, as measured at power electronics output terminals, is 9.6kW. With solar energy, from the reflective sunlight solar dish 21kW and measured output power from the power electronics 9.6kW, the conversion of solar energy to useful electric power an efficiency 46% (i.e. 9.6kW / 21kW). In addition, the design does not require external water / liquid for cooling.

Adsorption Characteristics of Modified MiL-101(Cr) for Gas (Mainly CH4) Storage Applications

As promising material for gas storage applications, MIL-101(Cr) can further be modified by doping with alkali metal (Li+, Na+, K+) ions. However, the doping concentration should be optimized below 10% to improve the methane adsorption. This article presents (i) the synthesis of MIL-101 (Cr) Metal Organic Frameworks, (ii) the characterization of the proposed doped adsorbent materials by X-ray Diffraction, Scanning Electron Microscopy, N2 Adsorption, Thermo-Gravimetric Analyzer, and (iii) the measurements of methane uptakes for the temperatures ranging from 125 K to 303 K and pressures up to 10 bar. It is found that the Na+ doped MIL-101(Cr) exhibits CH4 uptake capacity of (i) 295 cm3/cm3 at 10 bar and 160 K and (ii) 95 cm3/cm3 at 10 bar at 298 K. This information is important to design adsorbed natural gas (ANG) storage tank under ANG-LNG (liquefied natural gas) coupling conditions.

An Exergy-Based Analysis of Temperature Profiles for an Over-Pressure Reflow Oven Technology

In electronics assembly, the convection based soldering technologies in the production lines consumes massive resources and energy. The recent advancements in soldering technologies consume comparatively higher resources and needs to be optimized for resource efficient production which is also the motivation for the present work. This study is devoted to quantify the resource consumption and qualify this consumption through exergy flows in an over-pressure reflow technology as an energy intensive process in electronics manufacturing. The analysis implies on a big saving potential for energy consumption specifically during the over-pressure process which also defines the void reduction quality of solder joints. Exergy efficiency is the fraction of the work potential of the heat that is converted to work, and it illustrates the quality of consumed resources during the soldering oven process. Shortening the production lead-time, and increasing the production rate increase the efficiency of exergy and prevents wastage of usable energy. Furthermore, the set-up improvements for the temperature profiles are necessary, and the changes toward developing new technologies in pre-heating and over-pressure chamber zones are mandatory if a high efficiency of resources used is expected.