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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Simultaneous optimization of simulated moving bed adsorption and distillation for 2,3‐butanediol recovery

Abstract A combined simulated moving bed (SMB) and distillation separation scheme is developed to recover 2,3‐butanediol (BDO) from a dilute fermentation broth. The scheme was integrated into a lignocellulosic biorefinery that produces hydrocarbon fuels from corn stover with BDO as an intermediate. BDO recovery is one of the most challenging processes in this biorefinery; and given the high associated energy duties, direct distillation is considered cost‐prohibitive. An alternative separation is SMB adsorption in nanoporous materials, which can reject 90% of the water and reduce subsequent distillation costs. Rigorous models were used to optimize the SMB and distillation simultaneously. The separation can be added to the biorefinery while keeping the projected minimum fuel selling price (MFSP) below $0.66 USD (US dollars) per liter gasoline‐equivalent ($2.50/GGE, gallon gasoline equivalent). Finally, sensitivity analyses were conducted to assess the effects of cost and lifetime of the adsorbent, titer concentration, and BDO purity.

09 BIOMASS FUELS↗
DOE OSTI2024

Cost-optimal selection of pH control for mineral scaling prevention in high recovery reverse osmosis desalination

Conference proceedings for Foundations of Computer Aided Process Design (FOCAPD) 2024 that details a cost optimization model for pH control to prevent mineral scaling in high recovery reverse osmosis. This work applies a framework for incorporating detailed water chemistry predictions such as precipitation, pH change, and mineral scaling tendencies with process-scale optimization. It demonstrates that the acid choice for pH control can have a significant impact on pretreatment costs.

Amusat, Oluwamayowa↗
DOE OSTI2021

Storage Futures Study: Storage Technology Modeling Input Data Report

The Storage Futures Study (SFS) is a multiyear research project to explore the role and impact of energy storage in the evolving electricity sector of the United States. The SFS is designed to examine the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. This specific report synthesizes current and projected cost performance assumptions along with location availability for storage technologies through 2050 that will be used in scenario analysis for the SFS at both the bulk power and distribution system scales. For comparison and context, this report also presents a synthesis of current cost and performance characteristics of energy storage technologies for storage durations ranging from minutes to months and including mechanical, thermal, and electrochemical storage technologies for the electricity sector. This information is intended to cover a broad range of storage technologies that are currently receiving significant attention from the investment community as well as in the media. In the report, we emphasize that energy storage technologies must be described in terms of both their power (kilowatts [kW]) capacity and energy (kilowatt-hours [kWh]) capacity to assess their costs and potential use cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Multicriterion Benefit Evaluation of Deploying New Battery Technology with Increased Capacity at a Generic Nuclear Power

Nuclear power plant (NPP) safety improvements are routinely made by plant licensees and regulators. Examples of plant improvements include accident-tolerant fuel, diverse and flexible coping strategies, passive cooling systems, and increased battery capacity. A combined use of these plant improvements could lead to plant designs with enhanced resilience, allowing NPPs to better cope with both internal and external hazards and keep the plant operating safely, efficiently, and economically. This paper focuses on increased battery capacity and evaluates the potential costs and benefits of deploying batteries with increased capacities at a generic boiling water reactor (BWR) NPP. A multicriterion benefit evaluation methodology is used for the cost-benefit analysis. Ten alternatives for extending battery capacity are developed, including nine alternatives to provide additional direct-current power and one alternative to provide additional alternating-current power. Potential benefits of reducing plant risk are quantified through incorporating the alternatives into loss-of-offsite-power scenarios of the generic BWR probabilistic risk assessment model. Potential costs of implementing the alternatives are qualitatively discussed and ranked. The alternatives are then compared based on their impacts on plant risk and economics.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Multicriterion Benefit Evaluation of Deploying New Battery Technology with Increased Capacity at a Generic Nuclear Power Plant

This presentation is prepared for the DOE LWRS RISA Pathway Stakeholder Engagement Meeting on October 13-14, 2021. Nuclear power plant (NPP) safety improvements are routinely made by plant licensees and regulators. Examples of plant improvements include accident-tolerant fuel, diverse and flexible coping strategies, passive cooling systems, and increased battery capacity. A combined use of these plant improvements could lead to plant designs with enhanced resilience, allowing NPPs to better cope with both internal and external hazards and keep the plant operating safely, efficiently, and economically. This presentation focuses on increased battery capacity and evaluates the potential costs and benefits of deploying batteries with increased capacities at a generic boiling water reactor (BWR) NPP. A multicriterion benefit evaluation methodology is used for the cost-benefit analysis. Ten alternatives for extending battery capacity are developed, including eight alternatives to provide additional direct-current power and one alternative to provide additional alternating-current power. Potential benefits of reducing plant risk are quantified through incorporating the alternatives into loss-of-offsite-power scenarios of the generic BWR probabilistic risk assessment model. Potential costs of implementing the alternatives are qualitatively discussed and ranked. The alternatives are then compared based on their impacts on plant risk and economics.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Valuing EV Managed Charging for Bulk Power Systems

When and where electric vehicle (EV) charging occurs has significant implications for power systems supporting widespread EV adoption, especially with high shares of wind and solar generation. This study extends previous works by leveraging detailed simulation models for EV adoption, EV use, EV charging, and bulk power system operations, and by linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This technical potential study focuses on how the value of EV managed charging (EVMC) changes depending on charging flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and managed charging participation rate. We show that naively aggregating EV charging flexibility from individual vehicles into megawatt-scale resources grossly overestimates the flexibility of the fleet, because such aggregate models can unrealistically pair, e.g., one already-fully-charged vehicle's ability to increase load with another already-charging vehicle's ability to accept more charge, effectively requesting a charging rate that is infeasible for the latter vehicle. We find per-vehicle bulk system value is highest at low participation rates for all dispatch mechanisms. Factoring in production cost savings, avoided firm capacity savings, and combustion-related power sector emissions savings, we estimate the value of EVMC at low participation rates (5%) to be $33/vehicle-year to $69/vehicle-yr for within-session charging flexibility and $40/vehicle-yr to $120/vehicle-yr for within-week charging flexibility in an envisioned 2038 New England power system and monetary value reported in 2016 U.S. dollars. At 100% participation, per-vehicle value declines to $25/vehicle-yr to $31/vehicle-yr for within-session charging flexibility and to $29/vehicle-yr to $36/vehicle-yr for within-week charging flexibility; however, 100% participation yields the highest total system savings.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Integration of software tools for integrative modeling of biomolecular systems

Integrative modeling computes a model based on varied types of input information, be it from experiments or prior models. Often, a type of input information will be best handled by a specific modeling software package. In such a case, we desire to integrate our integrative modeling software package, Integrative Modeling Platform (IMP), with software specialized to the computational demands of the modeling problem at hand. After several attempts, however, we have concluded that even in collaboration with the software's developers, integration is either impractical or impossible. The reasons for the intractability of integration include software incompatibilities, differing modeling logic, the costs of collaboration, and academic incentives. In the integrative modeling software ecosystem, several large modeling packages exist with often redundant tools. So we reason, therefore, that the other development groups have similarly concluded that the benefit of integration does not justify the cost. As a result, modelers are often restricted to the set of tools within a single software package. The inability to integrate tools from distinct software negatively impacts the quality of the models and the efficiency of the modeling. As the complexity of modeling problems grows, we seek to galvanize developers and modelers to consider the long-term benefit that software interoperability yields. In this article, we formulate a demonstrative set of software standards for implementing a model search using tools from independent software packages and discuss our efforts to integrate IMP and the crystallography suite Phenix within the Bayesian modeling framework.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Boosting efficiency and reducing graph reliance: Basis adaptation integration in Bayesian multi-fidelity networks

The computational cost of high-fidelity numerical models makes outer-loop analysis, which requires repeated interrogation of the model such as uncertainty quantification, computationally demanding. Multi-fidelity methods, which construct a surrogate model using data from an ensemble of models of varying cost and accuracy, can substantially reduce the cost of outer-loop analysis. However, these methods can be difficult to apply when the model ensemble does not admit a clear hierarchy a priori and the correlations between models are low. Consequently, in this paper, we present a multi-fidelity method that leverages dimension reduction to enhance the correlation between models, thereby reducing the amount of data needed to train a surrogate from an unordered ensemble of models. Our method utilizes basis adaptation to build low-dimensional polynomial chaos expansions of each model and employs Multi-fidelity Networks to encode the relationships among models. We show that the resulting method exhibit two notable advantages over its counterpart: (1) enhanced accuracy (both reduced bias and variance); and (2) reduced dependency on the graph structure encoding relationships among models. We demonstrate the approach on an analytical test problem and a challenging finite element model for a spent nuclear fuel. Our method produces a surrogate model that is significantly more accurate than either a single-fidelity surrogate or a multi-fidelity surrogate constructed without basis adaptation.

42 ENGINEERING↗
DOE OSTI2020

Simulations and symmetries

ABSTRACT We investigate the range of applicability of a model for the real-space power spectrum based on N-body dynamics and a (quadratic) Lagrangian bias expansion. This combination uses the highly accurate particle displacements that can be efficiently achieved by modern N-body methods with a symmetries-based bias expansion which describes the clustering of any tracer on large scales. We show that at low redshifts, and for moderately biased tracers, the substitution of N-body-determined dynamics improves over an equivalent model using perturbation theory by more than a factor of two in scale, while at high redshifts and for highly biased tracers the gains are more modest. This hybrid approach lends itself well to emulation. By removing the need to identify haloes and subhaloes, and by not requiring any galaxy-formation-related parameters to be included, the emulation task is significantly simplified at the cost of modelling a more limited range in scale.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2020

Wind Tunnel Investigation of the Supersonic Stage Separation Aerodynamics of a Generic 0.0175-Scale Bimese Two-Stage-to-Orbit Reusable Launch Vehicle Configuration

A wind tunnel investigation was conducted of the supersonic stage separation aerodynamics of a generic two-stage-to-orbit bimese wingbody configuration in the NASA Langley Research Center Unitary Plan Wind Tunnel. Proximity and isolated model testing was conducted at Mach numbers of 2.3, 3.0, and 4.5 and a unit Reynolds number of 2.0 million per foot using 0.0175-scale models of the Langley Glide-Back Booster concept designated as the orbiter and booster in belly-to-belly and back-to-belly configurations. Longitudinal forces and moments were obtained on both models and surface static pressure measurements were obtained on the orbiter model at 328 relative proximity locations and at relative angles of attack of 0 degrees and 5 degrees. The test results supported a larger effort to develop and validate experimental and computational tools applicable to the design and simulation of stage separation and abort procedures for reusable launch vehicles composed of multiple bodies, including winged bodies. An initial proof-of-concept experiment featuring low-cost uninstrumented models was conducted to verify an emerging automated model control system and new support system hardware, and to identify potential model and support system blockage and unsteady aerodynamics/model dynamics prior to committing to higher-fidelity instrumented models. This investigation led to upgrades in the facility stage separation hardware, calibration and testing techniques and capabilities, and data analysis and documentation methodologies that have been extended to the more recent NASA Constellation and Space Launch System crew and cargo launch vehicle programs. A virtual diagnostics interface methodology was used to facilitate the design of the stage separation support hardware, to position the models in the test section, and to define the experimental test space. Advances in the facility automated model positioning system established a foundation for the development of a continuous-sweep data acquisition technique that is responsible for significant productivity improvements to the current NASA Space Launch System test program. The automated model positioning capability was leveraged to conduct a companion statistically-designed stage separation experiment requiring randomization of the relative proximity positions of the orbiter and booster models. The respective zones of influence and interference effects of the orbiter and booster were identified from three-dimensional scatter plots, contour and influence maps, and two-dimensional plotting methods. The highly-nonlinear, shock-dominated aerodynamic characteristics of the orbiter and booster in the Unitary Plan Wind Tunnel exhibited good agreement with independent test data obtained in a NASA Marshall Space Flight Center wind tunnel and with computational fluid dynamics predictions using a compressible, three-dimensional flow solver and an inviscid, unstructured Cartesian method.

Erickson, Gary E.↗
NASA NTRSDate not supplied

Strategies for Automation of Model Tuning in Multifidelity Trajectory Uncertainty Propagation

Multi-model Monte Carlo methods are efficient strategies to perform forward uncertainty quantification studies in entry, descent, and landing (EDL) applications. These multi-model methods are based on the classical Monte Carlo estimator, but fuse predictions from several low-fidelity models to obtain estimators with greater precision given a prescribed computational budget. The effectiveness of these approaches relies on the magnitudes of correlations between the low-fidelity models and the high-fidelity model, as well as the relative computational costs of all models. Identifying and exploiting the best trade-off between correlation and cost, which ultimately depends on the selection of hyperparameters in the low-fidelity models, is a task often performed by hand or simply inspired by the deterministic understanding available for a specific application. This work extends a preliminary effort,

Marten Thompson↗
DOE OSTI2026

plexosdb: A Modular Library for Programmatic PLEXOS Model Construction

plexosdb is a lightweight Python library for constructing PLEXOS models using a SQLite-backed data structure. It provides a clear, modular interface that maps relational data directly to model components. By leveraging SQLite and idiomatic Python, it enables fast iteration and reproducible workflows. The result is a performant, composable foundation for scalable PLEXOS model development.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1975

Stochastic model for fatigue crack size and cost effective design decisions

This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.

Hanagud, S.↗
DOE OSTI2025

DEVELOPMENT AND APPLICATION OF RISK ANALYSIS TOOLKIT FOR PLANT RESOURCE OPTIMIZATION

This paper presents the development of methods and tools that are being designed to optimize plant operations (e.g., maintenance/replacement schedules and optimal maintenance postures for plant components) in a manner that is more cost effective than current approaches and makes better use of available component health and cost data. These methods include both data- and model-based optimization methods. Model-based optimization methods directly include reliability and cost models to determine an optimal plant operational strategy. We consider gradient-based and evolutionary (based on genetic algorithms) optimization methods. The second class of methods target more specific use cases (e.g., project schedule optimization) and are not based on reliability models directly, but they require specific component reliability and cost data. This class of methods is based on variants of the knapsack problem with an aim to determine an optimal project schedule that maximizes the overall NPV. This paper also presents multi-objective methods designed to identify an optimal maintenance posture based on a Pareto frontier analysis. Rather than dictating the “right” tradeoff (i.e., identify the absolute best posture), we show how it is possible to perform a trade space exploration approach (i.e., identify value and costs of several postures and let the analysis account for desired value and cost metrics). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space. For all these methods we present detailed applicative examples that show their validity from a decision-making perspective.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A technoeconomic analysis of poly- and single-crystalline NMCxyz from material synthesis to battery pack design

A process model was developed for estimating the cost of manufacturing lithium nickel manganese cobalt oxide (LiNi x Mn y Co z O 2 , NMCxyz), the main cathode active material in lithium-ion batteries used for electric vehicles in the United States. The model was used to estimate the prices of NMC622, NMC811, and NMC955 with poly- and single-crystalline morphologies. The Battery Performance and Cost Model (BatPaC) was used to translate the NMC prices into battery pack prices. A decrease in cobalt content from NMC622 (20% Co) to NMC955 (5% Ni) decreases the material price by $\$$0.85/kg (−3%) due to a decrease in the cost of battery materials, which account for >60% of the total price. NMC622 only produce cheaper packs if the nickel sulfate cost is > 4 × its baseline, indicating higher nickel materials will lower pack cost under normal market conditions. Single-crystalline materials are $\$$2/kg (+8%) more expensive than their polycrystalline counterparts due to higher manufacturing costs from longer, hotter calcinations in less densely packed saggars. This increases the pack price by ∼$\$$3/kWh, assuming identical electrochemical properties. In conclusion, the single-crystalline materials could yield cheaper packs if cycled to higher upper cutoff voltages (i.e., 4.35 to 4.43 V for the single-crystalline material vs. 4.25 V for their polycrystalline counterparts).

Cost modeling↗
DOE OSTI2024

A Gaussian process autoregressive model capturing microstructure evolution paths in a Ni–Mo–Nb alloy

Additive manufacturing is increasingly being employed to produce components of complex geometries in structural alloys because of the expected energy savings associated with the near-net-shape capability and the ability to build in novel internal features that are not possible with many conventional manufacturing approaches. However, because of the extreme thermal conditions encountered, the non-equilibrium microstructures produced during powder bed-based additive manufacturing processes must be subjected to custom post-heat treatment processes to recover the target mechanical properties. Phase-field models and simulation techniques have matured to a state where the microstructure evolution paths, and the morphologies of the resulting precipitate phases can be predicted reasonably accurately, considering alloy-specific thermodynamic and kinetic aspects of the nucleation and growth processes. However, phase-field simulations are computationally intensive, which precludes the ability to apply the simulations directly to the length scale of the entire component. Therefore, it is highly desirable to develop low-computational-cost surrogate models that effectively capture the physics at the microstructural length scale, while facilitating the design of optimized processing conditions resulting in location-specific targeted microstructures at the component scale. The work presented here demonstrates the application of the materials knowledge system framework to develop a surrogate model that effectively captures the microstructural path during annealing of a Ni–Mo–Nb alloy containing different Mo and Nb compositions known to segregate during solidification under additive manufacturing conditions. Specifically, the surrogate model built in this work is based on a Gaussian process autoregressive model informed by statistical representation of simulated microstructures using two-point correlations and dimensionality reduction through principal component analysis. In conclusion, this surrogate model is shown to capture the bifurcation of the microstructural path during precipitation, which yields a microstructure dominated by the $\gamma^{\prime\prime}$ phase at high Nb concentrations and the $\delta$ phase at low Nb concentrations.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Cost optimization in low volume VLSI circuits

The relationship of integrated circuit (IC) cost to electronic system cost is developed using models for integrated circuit cost which are based on design/fabrication approach. Emphasis is on understanding the relationship between cost and volume for custom circuits suitable for NASA applications. In this report, reliability is a major consideration in the models developed. Results are given for several typical IC designs using off the shelf, full custom, and semicustom IC's with single and double level metallization.

Cook, K. B., Jr.↗
DOE OSTI2023

Designing Iowa Agricultural Landscapes to Improve Environmental Co-Benefits of Bioenergy Production

Cellulosic bioenergy feedstocks are needed to improve carbon (C) management while provisioning biomass for bioproducts and biofuel. The transition to increased cellulosic biomass production can be guided by land management plans designed to improve economic, environmental, and ecological performance. We constructed a sustainability model to compare landscape designs for biofuel production from corn (Zea mays L.) stover and switchgrass (Panicum virgatum L.) in central Iowa, USA. We used the model to compare environmental and socioeconomic outcomes associated with four landscape management strategies, with and without cellulosic biomass markets. We evaluated (1) a fuelshed area containing over 1.2 million ha (3 million acres) of corn and soybean (Glycine max (L.) Merr.) within 80 km (50 miles) of a commercial-scale cellulosic biorefinery in Nevada, Iowa, and (2) the South Fork watershed containing over 72,000 ha (178,000 acres) of these row crops within eight north central Iowa HUC-12 (hydrologic unit code) watersheds. At both landscape scales, we found that it is possible to achieve multiple environmental and socioeconomic benefits concomitantly with cellulosic biomass production by strategically collecting corn stover and converting the 10% of the lowest-profitability row crop land to perennial switchgrass. Potential benefits from landscape design include increased biodiversity, soil and water quality improvements, increased soil carbon sequestration for climate change mitigation, and reduced fertilizer use and cost. Our model results showed that increasing benefits can accrue when complementary conservation practices (e.g., reduced tillage, use of a rye cover crop) are combined and integrated throughout a fuelshed or watershed area. We conclude that ecologically based landscape designs offer valuable insights about costs and benefits of land management alternatives, with relevance for achieving stakeholder goals.

54 ENVIRONMENTAL SCIENCES↗