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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Optimal Control Prediction Method for Control Allocation

This paper proposes a novel prediction method for online optimal control allocation that extends the volume of moments achievable with the Moore-Penrose generalized inverse to the entire Attainable Moment Set. This method formulates the control allocation problem using selected basis vectors and associated gains which reduces the optimization problem dimensions and provides physical insight into the resulting optimal solutions. The proposed algorithm finds the entire family of unique optimal control solutions along the desired moment vector from the origin to the boundary of the Attainable Moment Set. Numerical results for the Moore-Penrose prediction method show that the unique minimal controls obtained yield the desired moment with near machine precision accuracy while maintaining control effectors within specified position limits. This method has been fully validated against the unique solution obtained on the boundary of the Attainable Moment Set using the Durham Direct Allocation method. Minimal control solutions obtained for moments in the interior of the Attainable Moment Set, similarly yield the desired moment to near machine precision while providing control solutions that are smaller (i.e. 2-norm) than solutions found with traditional control allocation algorithms (e.g. interior point methods) applied to the minimal control problem. Numerical simulations using a Matlab® autocoded executable (MEX) for the representative real world problem of 3-moments with 20 individual control effectors and prescribed control position limits show a mean computation speed of approximately 125 Hz which is sufficient to enable real-time flight allocation.

Acheson, Michael J.↗
DOE OSTI2017

Spanning the Core Design Space with Binary Perturbations - A Mathematical Investigation

A reactor core design engineer, even one with many years of experience or one using advanced fuel pattern optimization software, will likely fine tune the pattern before finalizing the design. Fine tuning can further minimize local enthalpy peaks, optimize reactivity to extend burnup, and add additional margin to limits on reactivity coefficients or heat flux. For reactors that have reached an equilibrium fuel cycle, the number of feeds each cycle is typically the similar to previous cycles as is their placement in the core. It is then the engineer's responsibly to efficiently select the placement of burned assemblies to ensure optimal fuel utilization, satisfy safety limits, and meet cycle energy requirements. One of the engineer's most commonly used tools in this fine tuning investigation is to swap the positions of two assemblies, most likely two previously irradiated ('burned') assemblies since their reactivity is lower than fresh fuel. Such an operation is referred to in this work as a binary perturbation or a 'swap'. If quarter core symmetry is maintained, the perturbation translates to the other three quadrants. Likewise if eighth core symmetry is maintained, the perturbation translates to other seven octants. The question is then, how much of the core design space can binary perturbations possibly span? This work seeks to quantitatively define the space spanned by m number of binary perturbations as a function of variable size through combinatorial principles and computer simulation. The results of this study are useful in understanding the in-core fuel management problem faced by both professionals who employ hand manipulations and those who attempt stochastic solutions of the problem.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Accelerated development of CuSbS 2 thin film photovoltaic device prototypes

Development of alternative thin film photovoltaic technologies is an important research topic because of the potential of low-cost, high-efficiency solar cells to produce terawatt levels of clean power. However, this development of unexplored yet promising absorbers can be hindered by complications that arise during solar cell fabrication. Here, a high-throughput combinatorial method is applied to accelerate development of photovoltaic devices, in this case, using the novel CuSbS2 absorber via a newly developed three-stage self-regulated growth process to control absorber purity and orientation. Photovoltaic performance of the absorber, using the typical substrate CuInxGa1 - xSe2 (CIGS) device architecture, is explored as a function of absorber quality and thickness using a variety of back contacts. This study yields CuSbS2 device prototypes with ~1% conversion efficiency, suggesting that the optimal CuSbS2 device fabrication parameters and contact selection criteria are quite different than for CIGS, despite the similarity of these two absorbers. The CuSbS2 device efficiency is at present limited by low short-circuit current because of bulk recombination related to defects, and a small open-circuit voltage because of a theoretically predicted cliff-type conduction band offset between CuSbS2 and CdS. Overall, these results illustrate both the potential and limits of combinatorial methods to accelerate the development of thin film photovoltaic devices using novel absorbers.

14 SOLAR ENERGY↗
DOE OSTI2022

Breeding Realistic D‐Brane Models

Abstract Intersecting branes provide a useful mechanism to construct particle physics models from string theory with a wide variety of desirable characteristics. The landscape of such models can be enormous, and navigating towards regions which are most phenomenologically interesting is potentially challenging. Machine learning techniques can be used to efficiently construct large numbers of consistent and phenomenologically desirable models. In this work we phrase the problem of finding consistent intersecting D‐brane models in terms of genetic algorithms, which mimic natural selection to evolve a population collectively towards optimal solutions. For a four‐dimensional supersymmetric type IIA orientifold with intersecting D6‐branes, we demonstrate that unique, fully consistent models can be easily constructed, and, by a judicious choice of search environment and hyper‐parameters, of the found models contain the desired Standard Model gauge group factor. Having a sizable sample allows us to draw some preliminary landscape statistics of intersecting brane models both with and without the restriction of having the Standard Model gauge factor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Vegetable Oil Based Polyurethane Containing 1,2,3-Triazolium Functional Groups as Antimicrobial Wound Dressing

Preparation of antimicrobial polyurethane wound dressing membranes from a mixture of castor oil and a novel soybean oil-based polyol containing 1,2,3-triazolium rings (QTSBO) was described in this research. QTSBO was prepared through N-alkylation of 1,2,3-triazole functional soybean oil (TSBO) with methyl iodide, and TSBO was synthesized from an azidated soybean oil and propargyl alcohol through click reaction. The excellent tensile strength of these dressings under dry state and minimum deterioration of this property at fully hydrated state guaranteed the mechanical protection of wounds during the entire period of the healing process. The measured quantities of equilibrium water absorption and water vapor transmission rate for the optimized dressings confirmed the applicability of the selected formulations for the preservation of proper moist environment over low exuding wounds. The cyto-compatibility of dressings was verified by the excellent ability of the dressings to support the growth and proliferation of dermal fibroblasts. Due to the presence of 1,2,3-triazolium rings the dressing showed efficient antimicrobial activity against different bacterial and fungal stains. Therefore, these dressing could promote wound healing by preserving moist and hygienic environment over the wound bed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Heat transfer model for moving packed-bed particle-to-sCO 2 heat exchangers integrated with metal foams

Particle-to-supercritical carbon dioxide (sCO 2 ) heat exchangers (HXs) play a vital role in coupling heat transfer fluid (HTF) from high-temperature thermal receivers to power cycle working fluids (WF). Heat transfer enhancement is essential for adopting particle-based moving packed-bed heat exchangers (MPBHXs) in next-generation thermal energy storage (TES) systems, as MPBHXs usually exhibit low particle bed-to-wall heat transfer coefficients. High-porosity metal foams have shown their effectiveness in heat transfer enhancement. Here, this work presents a continuum heat transfer model to demonstrate the heat transfer enhancement in MPBHXs when the particle bed channel is filled with high porosity metal foams compared to open channel MPBHXs. The presence of metal foams increases the effective thermal conductivity in the particle channel and enhances the interstitial heat transfer coefficient between the moving particle bed and the stationary metal foams. The present model considers coupled two-dimensional (2D) heat transfer in the particle channel with metal foams and 1D heat transfer in the sCO 2 channel and the dividing wall. The temperature profiles for the particle bed, metal foam, dividing wall, and sCO 2 stream, as well as the local heat flux profiles between those, are studied in detail for various foam porosities, from which the particle bed-to-wall heat transfer coefficient, overall heat transfer coefficient, and total heat transfer rate for the MPBHX are determined. The effects of major MPBHX design and operating parameters on the particle bed-to-wall heat transfer coefficient and overall heat exchange capacity are thoroughly examined; thus, the MPBHX performance improvement with metal foams is quantified for each case. The present heat transfer model can provide valuable insights into the metal-foam MPBHX design and optimization, scale-up, and operating parameters selection.

42 ENGINEERING↗
DOE OSTI2018

Application of nanofiltration for Rare Earth Elements recovery from coal fly ash leachate: Performance and cost evaluation

Here this work evaluated nanofiltration (NF) as a potential step in the recovery process of Rare Earth Elements (REEs) from leachates of coal combustion fly ashes. A pre-treatment step, by pH adjustment and microfiltration (MF), has been studied to separate REEs by major elements. The individual and combined effects of applied pressure (12–24 bar) and NF feed acidity (pH 1.5–3.5) on rejection of six critical REEs and permeate flux have been investigated via response surface methodology (RSM). The resulting model equations were used to develop a cost model for the recovery chain, in order to select the optimum NF operating conditions. The optimization of the REE recovery chain, including pre-treatment and NF, was done with respect to the objective of maximizing the difference between NF concentrate economic value and treatment cost. NF with an appropriate MF pre-treatment has been effective in concentrating REEs from fly ash leachate, reaching the maximum potential gain at the optimum operating conditions of 12 bar and pH 3.5.

42 ENGINEERING↗
DOE OSTI2022

Optimal economic dispatch policy for prosumer with energy storage considering self-consumption demand

This paper analyzed the effects of self-consumption demand on the joint economic dispatch of prosumers (energy consumers who are also producers), particularly for prosumers with both energy storage and distributed energy sources (DERs). Studies in the existing literature on the economic dispatch scheduling policy of energy storage, mostly from the perspective of electricity merchants, do not address the impacts of self-consumption demand. However, due to the intermittent and high levels of uncertainty regarding DERs generation and the dynamic demand of the prosumer, production and consumption are not always simultaneous; there are two possible scenarios in each period depending on whether DERs generation can meet prosumers' self-consumption or not. Incorporating the self-consumption demand will pose modeling challenges since these two scenarios cannot occur simultaneously in each period, and different scenarios require different decisions for prosumers. Further, this paper analyzed the two scenarios separately to find the optimal storage scheduling strategy, and the results were combined to get the optimal global solution. We focused on prosumers' economic decision-making while considering self-consumption demand and the physical constraints of a battery based on dynamic programming. Our study showed that the feasible state of charge (SOC) range of storage can be segmented into several sub-ranges by SOC reference points under the above two scenarios. As a result, a prosumer's optimal scheduling can be uniquely and conveniently selected based on the sub-ranges within which the current SOC falls. The results, therefore, provided multistage decision-making guidance for prosumers with energy storage.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Whole-plant phenotypic engineering: moving beyond ratios for multi-objective optimization of nutrient use efficiency

Nutrient use efficiency (NUE) is typically measured as the ratio of yield to soil nutrient availability but ignores contributions of underlying plant traits. Relevant plant traits can be grouped as root acquisition efficiency, shoot radiation use efficiency, and plant metabolic efficiency. The intentional integration of these traits will lead to synergistic improvements of NUE. Recent progress in trait-focused research includes phenotyping root nutrient uptake rates and respiration, engineering reduced photorespiration, and identification of nutrient assimilation pathways. Traits need to be conceptualized in agricultural systems contexts to improve synchrony of plant demand and soil supply of nutrients, including consideration of crop mixtures. Use of simulation modeling and multi-objective optimization will allow accelerating NUE gains beyond selection for a single ratio.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Optimizing combination of liver-enriched transcription factors and nuclear receptors simultaneously favors ammonia and drug metabolism in liver cells

The HepG2 cell line is widely used in studying liver diseases because of its immortalization, but its clinical application is limited by its low expression of the urea synthesis key enzymes and cytochromes P450 (CYPs). On the basis of our previous work, we investigated the transcriptional regulation of arginase 1 (Arg1) and ornithine transcarbamylase (OTC) in HepG2 cells. We also screened for the optimal combination of liver enrichment transcription factors (LETFs) and xenobiotic nuclear receptors that can promote the expression of key urea synthases and five major CYPs in HepG2 cells. Thus, recombinant HepG2 cells were established. Results showed that C/EBPβ, not C/EBPα, could upregulate expression of Arg1 and PGC1α and HNF4α cooperatively regulate the expression of OTC. The two optimal combinations C/EBPβ+HNF4α+HNF6+PXR and C/EBPβ+HNF4α+HNF6+CAR were selected. Compared with the control cells, the recombinant HepG2 cells modified by the two optimal combinations exhibited enhanced ammonia metabolism and CYP enzyme activity. Moreover, the HepG2/(C/EBPβ+HNF4α+HNF6+PXR) cells more strongly reduced ammonia than any other combination tested in this study. The present work indicated that optimizing the combination of transcription factors will simultaneously promote hepatocyte ammonia metabolism and drug metabolism. The recombinant HepG2 liver cell line constructed by the optimal combination provided an improved alternative means for bioartificial liver applications and drug toxicity testing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Analytical method for measuring cosmogenic 35 S in natural waters

Here, cosmogenic sulfur-35 in water as dissolved sulfate ( 35 SO 4 ) has successfully been used as an intrinsic hydrologic tracer in low-SO 4 , high-elevation basins. Its application in environmental waters containing high SO 4 concentrations has been limited because only small amounts of SO 4 can be analyzed using current liquid scintillation counting (LSC) techniques. We present a new analytical method for analyzing large amounts of BaSO 4 for 35 S. We quantify efficiency gains when suspending BaSO 4 precipitate in Inta-Gel Plus cocktail, purify BaSO 4 precipitate to remove dissolved organic matter, mitigate interference of radium-226 and its daughter products by selection of high purity barium chloride, and optimize LSC counting parameters for 35 S determination in larger masses of BaSO 4 . Using this improved procedure, we achieved counting efficiencies that are comparable to published LSC techniques despite a 10-fold increase in the SO 4 sample load. 35 SO 4 was successfully measured in high SO 4 surface waters and groundwaters containing low ratios of 35 S activity to SO 4 mass demonstrating that this new analytical method expands the analytical range of 35 SO 4 and broadens the utility of 35 SO 4 as an intrinsic tracer in hydrologic settings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Mechanistic Interpretations and Insights for the Oxidative Dehydrogenation of Propane via CO 2 over Cr 2 O 3 /Al 2 O 3 Catalysts

Oxidative dehydrogenation (ODH) of alkanes using carbon dioxide as a soft oxidant has recently emerged as a potentially attractive alternative to steam cracking for the production of light olefins. To elucidate reaction pathways and their dependence on the operating conditions, CO 2 -assisted propane dehydrogenation over a redox-active Cr 2 O 3 /Al 2 O 3 catalyst was examined in a packed bed reactor as a function of temperature, Cr 2 O 3 /CO 2 feed ratio, and residence time. Previous ODH studies have largely focused on CO 2 -rich conditions with the aim of preventing coke formation. However, at T = 600 °C the present study finds that the use of propane-rich conditions (1 ≤ C 3 H 8 /CO 2 ≤ 2.5) maximizes propylene production and selectivity while maintaining catalyst stability. In this work, it is postulated that the selective Mars van Krevelen dehydrogenation process is optimized at these ratios. Excess CO 2 apparently promotes nonselective dehydrogenation and dry reforming pathways that generate additional CO, adversely impacting catalyst stability via the Bouduard reaction. This hypothesis is supported by complementary investigations of the reverse water gas shift reaction and thermodynamic analysis. The findings and methodology presented here are likely applicable to related ODH processes with other alkanes and redox-active catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Mechanistic Evidence for Ligand-Centered Electrocatalytic Oxygen Reduction with the Conductive MOF Ni 3 (hexaiminotriphenylene) 2

In this study, establishing catalytic structure-function relationships introduces the ability to optimize the catalyst structure for enhanced activity, selectivity, and durability against reaction conditions and prolonged catalysis. Here we present experimental and computational data elucidating the mechanism for the O 2 reduction reaction with a conductive nickel-based metal-organic framework (MOF). Elucidation of the O 2 reduction electrokinetics, understanding the role of the extended MOF structure in providing catalytic activity, observation of how the redox activity and pKa of the organic ligand influences catalysis, and identification of the catalyst active site yield a detailed O 2 reduction mechanism where the ligand, rather than the metal, plays a central role. More generally, familiarization with how the structural and electronic properties of the MOF influence reactivity may provide deeper insight into the mechanisms by which less structurally defined nonplatinum group metal electrocatalysts reduce O 2 .

2D materials↗
DOE OSTI2024

Quantitative Determination of Metal Ion Adsorption on Cellulose Nanocrystals Surfaces

Nanocellulose is a bio-based material that holds significant potential in the field of water purification. Of particular interest is their potential use as a key sorbent material for the removal of metal ions from solution. However, the structure of metal ions adsorbed onto cellulose surfaces is not well understood. The focus of this work is to determine quantitatively the three-dimensional distribution of metal ions of different valencies surrounding negatively charged carboxylate functionalized cellulose nanocrystals (CNCs) using anomalous small-angle X-ray scattering (ASAXS). These distributions can affect the water and ionic permeability in these materials. The data show that increasing the carboxylate density on the surface of the CNCs from 740 to 1100 mmol/kg changed the nature of the structure of the adsorbed ions from a monolayer into a multilayer structure. The monolayer was modeled as a Stern layer around the CNC nanoparticles, whereas the multilayer structure was modeled as a diffuse layer on top of the Stern layer around the nanoparticles. Within the Stern layer, the maximum ion density increases from 1680 to 4350 mmol of Rb + /(kg of CNC) with the increase in the carboxylate density on the surface of the nanoparticles. Additionally, the data show that CNCs can leverage multiple mechanisms, such as electrostatic attraction and the chaotropic effect, to adsorb ions of different valencies. By understanding the spatial organization of the adsorbed metal ions, the design of cellulose-based sorbents can be further optimized to improve the uptake capacity and selectivity in separation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cost of Deconstruction Depots for Diversified, Waste-Based Lignocellulosic Sugars Using Distillable Solvents

Transitioning to a bioeconomy that makes use of low-emission and waste feedstocks requires greater flexibility to accommodate seasonal variations and mitigate long-term storage challenges, such as material loss and fire risk. To achieve this goal, biomass deconstruction technologies must efficiently handle diverse feedstocks. Here, we assess the cost of using butylaminea distillable solventto deconstruct 22 different biomass feedstocks: 7 herbaceous, 9 woody, 4 food processing residues, and 2 blends. Lignocellulosic sugar production costs, based on current empirical data, range from $1.3 to 6.1/kg, suggesting that substantial improvements are required to compete with conventional sugars. The high solvent loading (850 g/kg of whole slurry) is a process bottleneck. Lowering the solvent loading to 59 g/kg of whole slurry, demonstrated in an L-scale reactor using poplar biomass, reduces the minimum sugar selling price by 33%. Solvent loading and recovery, solid loading, sugar yield, enzyme use, and delivered biomass cost all play key roles in reaching sugar production costs of $0.45-0.79/kg. Strategic feedstock blending to maximize carbohydrate content, process optimization to improve conversion efficiency, and the selection of low-cost feedstocks are important to advancing feedstock-flexible biorefineries.

TEA↗
DOE OSTI2025

Shaping Peptide Assemblies Using Multifaceted Cyclic Tectons

Constructing distinct biomacromolecular assemblies typically necessitates target-specific selection and engineering of building blocks alongside optimization of assembly conditions. The challenge lies in achieving diverse morphological outcomes using simple, shared modules under identical conditions, a hallmark of natural systems that remains elusive in synthetic approaches. Here, in this work, we present a molecular scaffold-based strategy to instruct the coassembly of the same set of peptides into a variety of nanostructures across multiple dimensions. We create trifaceted cyclic scaffolds to manipulate two pairs of dimeric coiled-coil peptides prior to coassembly. These scaffolds, with addressable and orthogonal modules, allow controlled exposure of their cohesive faces, directing the formation of nanotriangles and fibrillar and lamellar assemblies. By tuning interpeptide arrangements that dictate scaffold geometry, we construct nonstraight fibrils with tunable curvature, which are rarely observed before. Notably, these scaffolds exhibit plasticity in adapting the sizes and orientations of cohesive faces to different assembly morphologies. The resultant nanostructures are consistent with the design and simulation results, demonstrating the reliability and predictability of this approach. Multifaceted cyclic scaffolds bridge the intellectual and physical gaps between building peptides and assemblies, holding promise for endowing various existing assembly systems with high tunability and versatility.

assembly morphology↗