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Aeroelastic Trim Drag Optimization of Mach 0.745 Transonic Truss-Braced Wing Aircraft with Variable-Camber Continuous Trailing-Edge Flap

This paper presents an aeroelastic trim drag optimization study of the Mach 0.745 Transonic Truss-Braced Wing (TTBW) aircraft with the Variable-Camber Continuous Trailing-Edge Flap (VCCTEF). An aero-structural analysis solver VSPAERO with transonic small disturbance, integral boundary-layer, and wing-strut interference corrections coupled to finite-element code BEAM3D is developed to provide a rapid aircraft aeroelastic performance evaluation. The VSPAERO model has been validated against wind tunnel test data. Aeroelastic trim drag optimization studies are conducted for a VCCTEF configuration with 6-spanwise sections. Three different flight conditions corresponding to Mach 0.745 are selected for the TTBW aircraft aeroelastic trim drag optimization at the design and off-design cruise lift coefficients. The preliminary optimization results show that the TTBW aircraft with the optimized VCCTEF deflection achieves a drag reduction of about 9.1 counts, 5.9 counts, and 11.8 counts corresponding to the lift coefficients 0.68, 0.73, and 0.78, respectively. A high-fidelity CFD solver FUN3D is used to validate the aeroelastic trim drag optimization.

Aeroelastic trim drag↗

Critical differences between electron beam melted and selective laser melted Ti-6Al-4 V

Effective optimization of the production of Ti-6Al-4 V using AM requires a fundamental understanding of the relative importance of different microstructural features to the deformation and failure mechanisms, particularly features that vary between production methods. In this study, the tensile response and deformation mechanisms of electron beam melted (EBM) AM Ti-6Al-4 V material loaded in different orientations and produced using various powder sizes were compared to those of selective laser melted (SLM) AM Ti-6Al-4 V material. The density and morphology of pores, phase fractions, prior-β grains, and defect microstructures were evaluated using scanning electron microscopy, X-ray computed tomography, electron backscatter diffraction, and transmission electron microscopy before and after deformation. The results were used to evaluate the relative importance of each feature on strengthening, deformation, and failure initiation mechanisms. Results focused primarily on coarse-powder EBM materials indicated that phase distribution and defect density were most influential for determining material yield strength as well as maximum possible strain to failure. Porosity was lower overall in EBM Ti-6Al-4 V than in SLM, allowing for occasional increases in part strain to failure, but remained a limiting factor determining overall part ductility.

36 MATERIALS SCIENCE↗

Design of space-type electronic power transformers

Both open and encapsulated varieties of high reliability, low weight, and high efficiency moderate and high voltage transformers were investigated to determine the advantages and limitations of their construction in the ranges of power and voltage required for operation in the hard vacuum environment of space. Topics covered include: (1) selection of the core material; (2) preliminary calculation of core dimensions; (3) selection of insulating materials including magnet wire insulation, coil forms, and layer and interwinding insulation; (4) coil design; (5) calculation of copper losses, core losses and efficiency; (6) calculation of temperature rise; and (7) optimization of design with changes in core selection or coil design as required to meet specifications.

Ahearn, J. F.↗

Design for an integrated discipline operations control center for Space Station Freedom

This paper presents selected features of a human factors oriented plan for a Space Station Freedom (SSF) ground Discipline Operations Center (DOC) that is integrated with other work areas used by multidisciplinary life scientists. This combined facility is referred to as an integrated DOC or IDOC. This plan is based upon the assumption that there will be a constantly changing array of specialized equipment and procedures used by life sciences principal investigators (PI) on the ground which must be linked to SSF through various DOC systems. Other sites will also be able to communicate with SSF (Anon., 1992). It is also assumed that cost reduction will be a major design consideration and that one integrated structure will be less expensive to build and operate than two separate ones. Since both the DOC personnel and PIs will need to communicate with the flight crew aboard SSF, the general interconnect architecture of the PIs' communication linkage is considered here. Key human factor design elements of this plan include: a candidate facility layout which accommodates three (3), multipurpose, rapidly reconfigurable work areas (suites) and consequent user traffic flow considerations, a multimedia telecommunications support capability, functional (human) traffic flow, optimized internal illumination and acoustics requirements, selected volumetric and safety requirements, and other architectural design parameters.

Haines, Richard F.↗

Fundamental Studies of Bifunctional Catalysts for Tandem Reactions

During the past few years of our funding from DOE Basic Energy Sciences, we have focused on the catalytic conversion of biomass-derived 5-hydroxymethyl furfural (HMF) as a platform molecule for sustainable synthesis of value-added chemicals. The combination of the diene and aldehyde functionalities in HMF enables catalytic production of acetalized HMF derivatives with diol or epoxy reactants to allow reversible synthesis of norcantharimide derivatives upon Diels-Alder reaction with maleimides. Whereas the electron-withdrawing nature of aldehyde group inhibits the reactivity of diene group in HMF to undergo Diels-Alder reactions with dienophiles, by converting the aldehyde group in HMF to an electron-donating hydroxyl group, HMF can append maleimide-based chemicals through Diels-Alder coupling. Acetalization of HMF not only produces an electron-rich diene for Diels-Alder reaction, but it also alters the reversibility of acetal formation and thereby allows for the controlled release of chemicals by hydrolysis. Therefore, we synthesized various norcantharimide derivatives from biomass-derived HMF by acetalization over an acid catalyst, Amberlyst-15, followed by Diels-Alder reaction with maleimide. The norcantharimides release the starting materials by retro Diels-Alder reaction that is triggered by acetal hydrolysis under acidic (≤pH 3) conditions. In subsequent work, we explored the synthesis and properties of functional polyurethanes and polyesters with tunable properties from biomass-derived (HMF)-Acetone-HMF (HAH) monomers. HAH can be selectively hydrogenated over Cu and Ru catalysts to produce partially-hydrogenated HAH (PHAH) and fully-hydrogenated HAH (FHAH). HAH contains functional groups, including hydroxyl, furan, enone, and ketone functionalities, that can be exploited to further tune the polymer properties. The π-electron conjugation between the enone and furan groups in HAH monomer stabilizes the furan group to prevent the uncontrolled degradation of furans during reactions, such as etherification. Therefore, HAH is a renewable monomer that can be used to synthesize polymers, having high molecular weight, symmetric functionalities, an inexpensive production price, and being derived from renewable resources without competition with food resources. We demonstrated the synthesis of functional polyurethanes and a renewable polyester from HAH-derived monomers, and 4,4’-methylenebis(phenyl isocyanate) (MDI). We showed that it is essential to be able to selective hydrogenate C=C double bonds in HAH to be able to achieve effective Diels Alder reactions of the furan ring. Therefore, we studied the hydrogenation at temperatures from 313 – 393 K of HAH over Pd, Ru, and Cu based catalysts. HAH was selectively hydrogenated to produce partially-hydrogenated monomers (PHAH) over Cu and Ru catalysts and to fully-hydrogenated HAH monomers (FHAH) over the Ru catalyst. Pd based catalysts yielded a mixture of partially and fully hydrogenated monomers. Reaction kinetics models were employed to quantify the kinetic behavior for hydrogenation over Ru, Cu, and Pd catalysts. A 5-step pathway exhibited over Pd and Ru catalysts consists of both series and parallel reaction steps, where HAH is both converted to fully hydrogenated products sequentially via series reactions of partially hydrogenated intermediates, as well as converted directly in parallel reactions to form the fully hydrogenated products. In contrast, a 3-step pathway over the Cu catalyst consists only of the consecutive reaction steps, where the final product was formed via series reactions of intermediate products. Additionally, reaction over the Cu catalyst did not hydrogenate the furan rings of the HAH molecule and yielded a different final product than those hydrogenation over Pd and Ru catalysts. Using the results from our detailed reaction kinetics studies, we developed universal conditions for the maximum production of the various hydrogenated products for both batch and plug flow systems. In subsequent work, we employed reaction schemes to optimize the yields of products from selective hydrogenations of HAH in isopropanol solvent and in the presence of liquid water. Reaction schemes consisting of 7, 9, and 11 steps were examined to describe the rates of formation of the observed products and reaction intermediates for hydrogenation of HAH over Ru and Pd catalysts, and a 3-step scheme was studied over Cu catalysts. Rate constants and activation energies were calculated using these reaction schemes, and we then apply these reaction schemes to explore the effects of water addition on the hydrogenation pathways. The effects of water addition to isopropanol (IPA) solvents on the hydrogenation of HAH were markedly different over Pd, Ru, and Cu catalysts. Over the Pd catalyst, the addition of water to IPA increased hydrogenation rates and promoted hydrogenation of furan rings. The addition of water to IPA yielded significant carbon losses over the Ru catalyst, and slowed hydrogenation steps over Cu, while significantly inhibiting hydrogenation of the ketone group. This behavior opened routes toward increased production rates of PHAH=O (a partially hydrogenated form of HAH containing a C=O bond), a product in which the diene groups of the furan rings were not hydrogenated. Addition of water also allowed increased feed concentrations of HAH that were previously not possible in pure IPA solvents.

09 BIOMASS FUELS↗

A novel software and conceptual design of the hardware platform for intensity modulated radiation therapy

Purpose: To deliver high quality intensity modulated radiotherapy (IMRT) using a novel generalized sparse orthogonal collimators (SOCs), the authors introduce a novel direct aperture optimization (DAO) approach based on discrete rectangular representation. Methods: A total of seven patients—two glioblastoma multiforme, three head & neck (including one with three prescription doses), and two lung—were included. 20 noncoplanar beams were selected using a column generation and pricing optimization method. The SOC is a generalized conventional orthogonal collimators with N leaves in each collimator bank, where N = 1, 2, or 4. SOC degenerates to conventional jaws when N = 1. For SOC-based IMRT, rectangular aperture optimization (RAO) was performed to optimize the fluence maps using rectangular representation, producing fluence maps that can be directly converted into a set of deliverable rectangular apertures. In order to optimize the dose distribution and minimize the number of apertures used, the overall objective was formulated to incorporate an L2 penalty reflecting the difference between the prescription and the projected doses, and an L1 sparsity regularization term to encourage a low number of nonzero rectangular basis coefficients. The optimization problem was solved using the Chambolle–Pock algorithm, a first-order primal–dual algorithm. Performance of RAO was compared to conventional two-step IMRT optimization including fluence map optimization and direct stratification for multileaf collimator (MLC) segmentation (DMS) using the same number of segments. For the RAO plans, segment travel time for SOC delivery was evaluated for the N = 1, N = 2, and N = 4 SOC designs to characterize the improvement in delivery efficiency as a function of N. Results: Comparable PTV dose homogeneity and coverage were observed between the RAO and the DMS plans. The RAO plans were slightly superior to the DMS plans in sparing critical structures. On average, the maximum and mean critical organ doses were reduced by 1.94% and 1.44% of the prescription dose. The average number of delivery segments was 12.68 segments per beam for both the RAO and DMS plans. The N = 2 and N = 4 SOC designs were, on average, 1.56 and 1.80 times more efficient than the N = 1 SOC design to deliver. The mean aperture size produced by the RAO plans was 3.9 times larger than that of the DMS plans. Conclusions: The DAO and dose domain optimization approach enabled high quality IMRT plans using a low-complexity collimator setup. The dosimetric quality is comparable or slightly superior to conventional MLC-based IMRT plans using the same number of delivery segments. The SOC IMRT delivery efficiency can be significantly improved by increasing the leaf numbers, but the number is still significantly lower than the number of leaves in a typical MLC.

61 RADIATION PROTECTION AND DOSIMETRY↗

Shape Optimization by Bayesian-Validated Computer-Simulation Surrogates

A nonparametric-validated, surrogate approach to optimization has been applied to the computational optimization of eddy-promoter heat exchangers and to the experimental optimization of a multielement airfoil. In addition to the baseline surrogate framework, a surrogate-Pareto framework has been applied to the two-criteria, eddy-promoter design problem. The Pareto analysis improves the predictability of the surrogate results, preserves generality, and provides a means to rapidly determine design trade-offs. Significant contributions have been made in the geometric description used for the eddy-promoter inclusions as well as to the surrogate framework itself. A level-set based, geometric description has been developed to define the shape of the eddy-promoter inclusions. The level-set technique allows for topology changes (from single-body,eddy-promoter configurations to two-body configurations) without requiring any additional logic. The continuity of the output responses for input variations that cross the boundary between topologies has been demonstrated. Input-output continuity is required for the straightforward application of surrogate techniques in which simplified, interpolative models are fitted through a construction set of data. The surrogate framework developed previously has been extended in a number of ways. First, the formulation for a general, two-output, two-performance metric problem is presented. Surrogates are constructed and validated for the outputs. The performance metrics can be functions of both outputs, as well as explicitly of the inputs, and serve to characterize the design preferences. By segregating the outputs and the performance metrics, an additional level of flexibility is provided to the designer. The validated outputs can be used in future design studies and the error estimates provided by the output validation step still apply, and require no additional appeals to the expensive analysis. Second, a candidate-based a posteriori error analysis capability has been developed which provides probabilistic error estimates on the true performance for a design randomly selected near the surrogate-predicted optimal design.

Patera, Anthony T.↗

Schedule Management Optimization (SMO) Domain Model (V.1.2)

Schedule Management Optimization (SMO) is a tool for automatically generating a schedule of project tasks. Project scheduling is traditionally achieved with the use of commercial project management software or case-specific optimization formulations. Commercial software packages are useful tools for managing and visualizing copious amounts of project task data. However, their ability to automatically generate optimized schedules is limited. Furthermore, there are many real-world constraints and decision variables that commercial packages ignore. Case-specific optimization formulations effectively identify schedules that optimize one or more objectives for a specific problem, but they are unable to handle a diverse selection of scheduling problems. SMO enables practitioners to generate optimal project schedules automatically while considering a broad range of real-world problem characteristics. SMO has been designed to handle some of the most difficult scheduling problems – those with resource constraints, multiple objectives, multiple inventories, and diverse ways of performing tasks. This report contains descriptions of the SMO modeling concepts and explains how they map to real-world scheduling considerations.

97 MATHEMATICS AND COMPUTING↗

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parameters as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about 28% of incremental oil recovery. The sensitivity analysis reduced the number of control variables to decrease computational time. A risk aversion factor was used to represent results at various confidence levels to assist management in the decision-making process. The defined objective functions were proved to be a robust approach to co-optimize oil recovery and CO 2 storage. The Farnsworth CO 2 project will serve as a benchmark for future CO 2 –EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.

54 ENVIRONMENTAL SCIENCES↗

Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

Holst, Terry L.↗

Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

A genetic algorithm approach suitable for solving multi-objective problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding Pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the Pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide Pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

Holst, Terry L.↗

Integrated Design and Manufacturing Analysis for Automated Fiber Placement Structures

Automated fiber placement provides many advancements beyond traditional hand layups in terms of efficiency and reliability. However, there are also a variety of unique challenges that arise with automated fiber placement technology. In particular, steering of tows over doubly-curved tool surfaces can result in material overlaps and gaps due to path convergence/divergence, fiber angle deviation, as well defects in the tows themselves such as puckers and wrinkles. Minimization of these defects is traditionally considered a task for the manufacturing discipline. Manufacturing specifications are often created for these defects based on laminate testing and can be inflexible to avoid more tests. Recent efforts have been made under the National Aeronautics and Space Administration (NASA) Advanced Composites Project (ACP) to develop software tools and processes that provide automated coupling between design and manufacturing disciplines. The objective of this coupling is to provide information to the design discipline on the manufacturability of a laminate while the laminate is being designed. A variety of software tools, both existing commercial tools and research tools under development, will be used to achieve this objective: HyperSizer for laminate optimization, the Computer Aided Process Planning module for selection of manufacturing process parameters, Vericut Composite Programming for tow path simulation, and COMPRO for deposition and cure defects. The newly developed “Central Optimizer” tool will be used to tie the modules together and drive the design for manufacturing process.

Noevere, August↗

Evaluation of Hydrogen Production Feasibility for a Light Water Reactor in the Midwest

Increased electricity production from renewable energy resources coupled with low natural gas prices has caused existing light-water reactor (LWRs) to experience ever diminishing returns from the electricity market. Via partnership among Idaho National Laboratory (INL), The National Renewable Energy Laboratory (NREL), Argonne National Laboratory (ANL), Exelon, and Fuel Cell Energy a techno-economic analysis on the viability of retrofitting existing pressurized water reactors (PWRs) to produce hydrogen (H2) via high temperature steam electrolysis (HTSE) has been conducted. Such integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long-term. To accommodate such an integration, a detailed analysis of HTSE process operation, requirements, and flexibility was conducted. Technical analysis includes proposed nuclear system control scheme modifications to allow dynamic operation of the HTSE via both thermal and electrical connection to the nuclear plant. High fidelity Modelica simulations showcase the viability of such control schemes. However, due to limited knowledge of solid oxide fuel cell (SOFC) stack degradation due to thermal gradients; thermal cycling of the HTSE was not included. Therefore, the control schemes proposed are only utilized to re-distribute steam at startup and only the portion of electricity utilized in the electrolyzers is cycled. From the detailed analysis of the nuclear integration and the HTSE process design, a comprehensive cost estimation was conducted in the APEA and H2A models to elucidate capital and operational costs associated with the production, compression, and distribution of hydrogen from a nuclear facility. Alongside this costing analysis, market analyses were conducted by NREL and ANL on the electric and hydrogen markets respectively in the PJM interconnect. Utilizing the electricity data market projections in the PJM interconnect from NREL and hydrogen demand/pricing projections from ANL a five variable sweep over component capacities, discount rates, and hydrogen pricing was completed using the stochastic framework RAVEN (Risk Analysis Virtual ENVironment) through its resource dispatch plugin HERON (Heuristic Energy Resource Optimization Network). Each combination of variables was evaluated stochastically four times over a seventeen year timespan from 2026-2042 (inclusive) to determine the most economically advantageous solution. Following the five variable sweep an optimization was conducted about the best sweep point to determine optimal component sizing and setpoints. Results suggest positive gain is achievable at all projected hydrogen market pricing levels and at all discount rates. However, exact component sizing and net returns vary based on these values and if incorrect sizing is selected; major net losses can occur. The optimal result occurred with set points as follows: high hydrogen prices, the largest possible HTSE unit in the sweep set at 7.47 kg/sec [645.4 tpd], a contractual hydrogen market agreement 7.29 kg/sec [629.8 tpd], and a hydrogen storage size 115,188 kg. The analysis suggested that with a discount rate of 8%, a ΔNPV = 1.2 billion over the seventeen year span can be achieved. The results illuminate that by operating in multiple markets the nuclear facility is capable of avoiding sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted in this report is a differential cash flow analysis and as such does not present profit levels. Instead it highlights the net benefit between building and competing in the hydrogen market utilizing nuclear facilities and conducting business as usual in the electricity markets. Additionally, results presented in this report exhibit conservatism due to four key assumptions: Given the limited knowledge on SOFC stack degradation due to thermal gradients the high temperature steam electrolysis plant is not allowed to thermally cycle. This limitation decreases electricity generation capacity in the nuclear plant, reducing capacity payments and the maximum output to the electrical grid. This analysis considers building a separate hydrogen pipeline for use in the nuclear facility. Research is currently being conducted to determine if existing natural gas pipelines can accommodate direct hydrogen injection. If hydrogen can be integrated into existing natural gas pipelines then a capital savings of ~$19,000,000 per kg/sec [1 kg/sec = 86.4 tpd] of installed HTSE capacity could be realized. Fast transients in the electric grid are typically served by flywheels and electric batteries. With electrolysis only operation the nuclear plant can flex its electricity just as quickly. However, for this analysis, the ancillary services market has been neglected. Should the nuclear plant have the ability to operate in the ancillary services market during periods when it is producing hydrogen, an additional substantial income stream that would increase overall system profitability could be considered. Subsidies for non-emitting generation technologies are not introduced in the cash flow analysis, but instead are completed assuming zero subsidies. Profitability is based solely on electricity pricing. Electric pricing is assumed to never go negative. Instead, it is assumed overall system curtailment by the Independent System Operator (ISO) will occur in such a manner that pricing remains at or above zero. This assumption inflates the “business as usual” scenario, thus decreasing the ΔNPV calculated. If negative pricing scenarios continue to occur as they do today, one would expect a further increase in ΔNPV. Overall, results advocate that, through market diversification, nuclear power plants have the potential to substantially increase current profit margins, increase market penetration, and ultimately solidify their place as a mainstay in energy production.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Sensitivity analysis of an automated fault detection algorithm for residential air-conditioning systems

The state of the art of fault detection and diagnosis (FDD) for residential air-conditioning systems is expensive and not yet amenable to widespread implementation. FDD for homes can significantly reduce utility costs, and increase the lifespan of the equipment. The cost barriers currently, however, make FDD for homes economically unviable for large scale implementation. In prior work, we offered a solution to reduce FDD costs by proposing an automated fault detection algorithm to serve as a screening step before more expensive FDD tests can be conducted. The algorithm uses only the home thermostat and local weather information to identify thermodynamic parameters and detect high-impact air-conditioning faults, including those that occur during equipment installation. We had tested the algorithm on a single EnergyPlus™ model of a home in Orlando, Florida. The thermodynamic parameter identification process is highly nonconvex involving several local optimal solutions. In this paper we propose a novel method to select the best model for fault detection from among the list of local optimal solutions to make the algorithm more robust to homes of different construction, without which the fault detection process would be infeasible. Another unique contribution of the paper is implementing the solution on real-world data. We also bring the algorithm closer to market by testing it on real-world data. We implement the algorithm on data obtained from experiments conducted by the Florida Solar Energy Center (FSEC) on a laboratory home equipped with a heat pump where faults were intentionally added for a period of seven months. The algorithm successfully detected an undercharge fault with 70.6% accuracy, concurrent duct leakage and undercharge faults with 85.2% accuracy, and duct leakage faults with 69.1% accuracy. A sensitivity analysis is also performed on EnergyPlus models of nine types of homes that vary in construction to demonstrate the robustness of the algorithm. Finally, the algorithm achieves an average accuracy of 71% for no-fault condition, 77% for 40% undercharge fault, and 76% for duct-leak fault.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗

Establishment of CRISPR/Cas9-Mediated Knock-in System for Porcine Cells with High Efficiency

Since the birth of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9, the new genome engineering technology has become a hot topic in the scientific community. However, for swine, the system of pig cells’ homology directed repair (HDR) is generally unstable and costly. Here, we aim to make knock-in of porcine cells more realizable. The Rosa26 locus was chosen for gene editing. Through the optimization of strategy, an efficient sgRNA was selected by TIDE analysis. Correspondingly, a vector system was constructed for gene insertion in pRosa26 locus by homologous recombination. A large percentage of cells whose gene is edited easily result in apoptosis. To improve the positive rate, culturing systems have been optimized. Sequence alignment and nuclear transfer confirmed that we got two knock-in cell lines and transgene primary porcine fetal fibroblasts (PFFs) successfully. Results showed that the gene editing platform we used can obtain genetically modified pig cells stably and efficiently. This system can contribute to pig gene research and production of transgenic pigs.

60 APPLIED LIFE SCIENCES↗

Advanced Nuclear Technology. Using Technology for Small Modular Reactor Staff Optimization, Improved Effectiveness, and Cost Containment, 3002007071

Through this grant, the U.S. Department of Energy (DOE) will review several functional areas within a nuclear power plant, including fire protection, operations and operations support, refueling, training, procurement, maintenance, site engineering, and others. Several functional areas need to be examined since there appears to be no single staffing area or approach that alone has the potential for significant staff optimization at new nuclear power plants. Several of the functional areas will require a review of technology options such as automation, remote monitoring, fleet wide monitoring, new and specialized instrumentation, human factors engineering, risk informed analysis and PRAs, component and system condition monitoring and reporting, just in time training, electronic and automated procedures, electronic tools for configuration management and license and design basis information, etc., that may be applied to support optimization. Additionally, the project will require a review key regulatory issues that affect staffing and could be optimized with additional technology input. Opportunities to further optimize staffing levels and staffing functions by selection of design attributes of physical systems and structures need also be identified. A goal of this project is to develop a prioritized assessment of the functional areas, and R&D actions needed for those functional areas, to provide the best optimization

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Emulation of Synaptic Plasticity in WO 3 ‐Based Ion‐Gated Transistors

Neuromorphic systems, inspired by the human brain, promise significant advancements in computational efficiency and power consumption by integrating processing and memory functions, thereby addressing the von Neumann bottleneck. This paper explores the synaptic plasticity of a WO3-based ion-gated transistor (IGT) in [EMIM][TFSI] and a 0.1 mol L −1 LiTFSI in [EMIM][TFSI] for neuromorphic computing applications. Cyclic voltammetry (CV), transistor characteristics, and atomic force microscopy (AFM) force–distance (FD) profiling analyses reveal that Li + brings about ion intercalation, together with higher mobility and conductance, and slower response time (τ). WO 3 IGTs exhibit spike amplitude-dependent plasticity (SADP), spike number-dependent plasticity (SNDP), spike duration-dependent plasticity (SDDP), frequency-dependent plasticity (FDP), and paired-pulse facilitation (PPF), which are all crucial for mimicking biological synaptic functions and understanding how to achieve different types of plasticity in the same IGT. The findings underscore the importance of selecting the appropriate ionic medium to optimize the performance of synaptic transistors, enabling the development of neuromorphic systems capable of adaptive learning and real-time processing, which are essential for applications in artificial intelligence (AI).

36 MATERIALS SCIENCE↗