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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrated Biomass Supply Analysis and Logistics Model (IBSAL) 2.0

The Integrated Biomass Supply Analysis and Logistics (IBSAL) 2.0 models a feedstock supply shed's harvest and transport process to estimate the cost of delivered feedstock. The model sets up a supply shed of fields, harvests the fields using a series of sequential harvest operations with different crew types, and transports the harvested feedstock to a storage facility or refinery. The model reports many metrics; the most important ones include the crew resources required for harvest and transport operations, equipment utilization, fuel usage, amount of dry mass harvested, the cost for each operation, and the expected time to complete the harvest with the provided resources. IBSAL 2.0 is a complete redesign around the ExtendSim database, and it is faster and easier to reapply the model to different feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2023

Hydropower Value Drivers

Conventional hydro resources generate the majority of their value by providing energy under most conditions, but the relative fraction of value generated by providing ancillary services and capacity increases with increasing penetration of resources with zero fuel costs. Pumped storage hydropower resources generate the majority of their value by providing capacity under most conditions, but the relative fraction of value generated by providing energy increases with increasing penetration of resources with zero fuel costs. The total value of conventional hydropower generally decreases in systems with increasing penetration of resources with zero fuel costs; this is largely due to the associated decrease in average energy prices. The total value of pumped storage generally increases in systems with increasing penetration of resources with zero fuel costs, largely due to opportunities to operate in pumping mode when energy prices are low or even negative. Energy storage representation must be enhanced to ensure that models accurately capture system value streams for these resources. Current power system models have a limited ability to capture the price dynamics of ancillary services, and it is still challenging to assess the role and magnitude of ancillary service value streams in future systems. Power systems are currently in a state of rapid and dramatic evolution due to a number of different factors, including the increasing penetration of variable renewable energy (VRE) sources, such as wind and solar, and battery energy storage systems (BESS). This evolution will change the way power systems are fundamentally planned and operated. Some of these changes may be incremental, while others may be more significant, but the result will likely be parallel evolution in the definition and requirement of different grid services and therefore a subsequent shift in their relative values. This report presents a framework developed to identify such system value drivers and quantify their relative impact on several different value streams, with a specific focus on implications for conventional hydropower and pumped storage hydropower (PSH) resources. This value drivers framework (VDF) encompasses five core analytical steps: 1. Identify potential drivers and develop scenarios, 2. Execute production cost models, 3. Calibrate prices, 4. Optimize hydropower operations, and 5. Quantify value drivers.

13 HYDRO ENERGY↗
DOE OSTI2022

Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT)

This report provides technical documentation and background on the newly-developed Wind Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT) software. WOMBAT is an open-source model that can be used to obtain cost estimates for operations and maintenance of land-based or offshore wind power plants. The software was designed to be flexible and modular to allow for implementation of new strategies and technological innovations for wind plant maintenance. WOMBAT uses a process-based simulation approach to model day-to-day operations, repairs, and weather conditions. High-level outputs from WOMBAT, including time-based availability and annual operating costs, are found to agree with published results from other models.

17 WIND ENERGY↗
NASA NTRS2019

Building an Economical and Sustainable Lunar Infrastructure to Enable Human Lunar Missions

To enable return of human missions to the surface of the Moon sustainably, a new study was initiated to assess the feasibility of developing an evolvable, economical and sustainable lunar surface infrastructure using a public-private partnerships approach. This approach would establish partnerships between NASA and private industry to mutually develop lunar surface infrastructure capabilities to support robotic missions initially and later evolve to full-scale commercial infrastructure services in support of human missions. These infrastructure services may range from power systems, communication and navigation systems, thermal management systems, mobility systems, water and propellant production to life support systems for human habitats. The public-private partnerships approach for this study leverages best practices from NASA's Commercial Orbital Transportation Services (COTS) program which introduced a new innovative and economical approach for partnering with industry to develop commercial cargo transportation services to the International Space Station (ISS). In this approach, NASA and industry partners shared cost and risk throughout the development phase which led to dramatically reducing development and operations costs of these transportation services. Following this approach, a Lunar COTS concept was conceived to follow this model and gradually develop cost-effective surface infrastructure capabilities in partnership with industry to provide economical, operational services for small-scale robotic missions. To support human missions, this work has now been extended to analyze full-scale lunar infrastructure systems. This infrastructure system will have capabilities to support human missions from a few days to several months and will also maximize the use of existing lunar resources, such as, water from ice deposits at the lunar poles. The plan includes a gradual buildup of these capabilities using a phased-development approach that will eventually lead to operational infrastructure services. By partnering with industry to develop and operate the infrastructure services using the COTS model, this plan will also result in significant cost savings, reduced risk and increased reliability. This paper will describe the Lunar COTS concept goals, objectives and approach for developing an evolvable, economical and sustainable human lunar infrastructure as well as the challenges and opportunities for development.

Lunar Surface Systems↗
NASA NTRS1983

A multi-item maintenance center inventory model for low-demand reparable items

In many military and commercial contexts, complex equipment undergoes scheduled maintenance overhauls at regular intervals during which all failed components are replaced. Failure to have replacements on hand for all failed parts requires emergency measures at premium cost. When reparable parts are highly reliable and expensive, both holding and shortage costs are high. This model determines the reparable parts inventory for a maintenance center under three alternative criteria: (1) maximizing job-completion rate subject to constraint on total holding costs, (2) minimizing total holding costs plus expected job noncompletion costs, and (3) minimizing total holding costs subject to a required minimum job-completion rate. Exact solutions may be obtained using dynamic programming. Approximate solutions, found easily by marginal analysis, have readily computed bounds on possible error. The solution methods for the three formulations are illustrated in a simple example.

Schaefer, M. K.↗
DOE OSTI2024

Cost Analysis and Projections for U.S.-Manufactured Automotive Lithium-ion Batteries

This document reports on a study conducted to estimate the cost of U.S-produced automotive battery packs for model years (MY) 2023 to 2035, using Argonne National Laboratory’s BatPaC tool. The costs were estimated by designing batteries for several classes of vehicles for four discrete model years (2023, 2026, 2030, and 2035), where a representative battery technology and material prices are selected based on information available today. Correlations were developed from the four discrete years to enable annual pack cost estimates as a function of pack size (kWh) and model year. A consolidated cost curve was then developed that includes battery size, technology by model year, and the anticipated sales volumes of each class of vehicles over the years. This cost curve estimates the volume-averaged, U.S.-manufactured battery pack cost of PHEVs and BEVs in the United States to be $\$140$/kWh for the model year 2023, which will reduce to $\$86$/kWh in MY2035. Applying tax credits from section 45X of the Inflation Reduction Act can further reduce the average pack cost to as low as $\$56$/kWh in MY2029. The report also includes several sensitivity studies that investigate the effect of pack production volume, material prices, fast charge requirements, and labor rates.

25 ENERGY STORAGE↗
DOE OSTI2020

Chiral three-nucleon force and continuum for dripline nuclei and beyond

Three-nucleon force and continuum play important roles in reproducing the properties of atomic nuclei around driplines. Therefore it is valuable to build up a theoretical framework where both effects can be taken into account to solve the nuclear Schrödinger equation. To this end, in this letter, we have expressed the chiral three-nucleon force within the continuum Berggren representation, so that bound, resonant and continuum states can be treated on an equal footing in the complex-momentum space. To reduce the model dimension and computational cost, the three-nucleon force is truncated at the normal-ordered two-body level and limited in the sd-shell model space, with the residual three-body term being neglected. We choose neutron-rich oxygen isotopes as the test ground because they have been well studied experimentally, with the neutron dripline determined. The calculations have been carried out within the Gamow shell model. The quality of our results in reproducing the properties of oxygen isotopes around the neutron dripline shows the relevance of the interplay between three-nucleon force and the coupling to continuum states. We also analyze the role played by the chiral three-nucleon force, by dissecting the contributions of the 2π exchange, 1π exchange and contact terms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Assimilation of Multiscale Data into Multifidelity Biogeochemical Models (Final Report)

Quantitative predictions of subsurface processes rely on computational models that capture, with different degrees of fidelity, complex interactions between hydrologic and biogeochemical processes. Molecular- and pore-scale models provide a high-fidelity representation of these processes but are impractical at the field scale. Reduced complexity (e.g., field-scale or data-driven) models sacrifice some degree of fidelity in favor of computational efficiency. Uncertainty and assimilation of data into model predictions, pose a question of model selection: Given a significant difference in computational cost, can a lower-fidelity model be preferable to its higher-fidelity counterpart? Since a predictive model must be computable in reasonable time it has to operate at the field scale, with molecular- and pore-scale data (obtained either from simulations or measurements) determining both the model's structure and parameters. Availability of such multi-resolution data raises a question hitherto undressed in hydrogeology: Can a coarse model dynamically ``learn'' its own structure (e.g., adjust the reaction pathways in its transport module) as more fine-scale data become available during simulations? Our results in multifidelity simulations, data assimilation, and machine learning led us to hypothesize that the answer to these questions is ``yes''. The overarching goal of this project was to confirm this hypothesis by developing scalable, computationally efficient tools for assimilation of data into multiscale models, in which fine-scale data and simulations dynamically inform and autonomously modify coarse-scale models. Our research led to nine manuscripts, three of which have been published and the other six are currently under review.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Testing Recommendations for Thermal Failure Analysis

Minimizing ranges of uncertainty in failure QOIs is vital for making informed engineering decisions. To improve our decision-making ability, it is necessary to have a QOI representation that captures more complex failure modes. Capturing the physics of complex time-dependent temperature failure in explicit detail can be computationally and experimentally expensive. To avoid this blooming of complication and costs, an empirical QOI component-level failure/damage model may be sufficient to help identify component-level failure. In this context, failure and damage are abstractions of more complicated processes that lead to the cessation of normal operating behavior, not a representation of mechanical damage, such as void formation. Such a model requires minimal increases in computational cost and experimental burden. The proposed QOI serves as an indicator that something has likely failed, similar to the previous critical failure temperatures or pressures. This QOI will not replace any existing failure QOIs. It will be calculated alongside them, allowing for preservation of legacy style QOI measurements with new context from the new QOI.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Foundations of the Bandera Abstraction Tools

Current research is demonstrating that model-checking and other forms of automated finite-state verification can be effective for checking properties of software systems. Due to the exponential costs associated with model-checking, multiple forms of abstraction are often necessary to obtain system models that are tractable for automated checking. The Bandera Tool Set provides multiple forms of automated support for compiling concurrent Java software systems to models that can be supplied to several different model-checking tools. In this paper, we describe the foundations of Bandera's data abstraction mechanism which is used to reduce the cardinality (and the program's state-space) of data domains in software to be model-checked. From a technical standpoint, the form of data abstraction used in Bandera is simple, and it is based on classical presentations of abstract interpretation. We describe the mechanisms that Bandera provides for declaring abstractions, for attaching abstractions to programs, and for generating abstracted programs and properties. The contributions of this work are the design and implementation of various forms of tool support required for effective application of data abstraction to software components written in a programming language like Java which has a rich set of linguistic features.

Hatcliff, John↗
NASA NTRS2006

Towards a Framework for Modeling Space Systems Architectures

Topics covered include: 1) Statement of the problem: a) Space system architecture is complex; b) Existing terrestrial approaches must be adapted for space; c) Need a common architecture methodology and information model; d) Need appropriate set of viewpoints. 2) Requirements on a space systems model. 3) Model Based Engineering and Design (MBED) project: a) Evaluated different methods; b) Adapted and utilized RASDS & RM-ODP; c) Identified useful set of viewpoints; d) Did actual model exchanges among selected subset of tools. 4) Lessons learned & future vision.

cost savings↗
NASA NTRSDate not supplied

Quantum-Compatible Variational Segmentation for Image-to-Image Wildfire Detection Using Satellite Data

Wildfire occurrences have been increasing for the past decade, leaving devastating traces across the world. In the recent efforts, remote sensing and airborne missions have been utilized to better understand and manage wildfires. This has resulted in an exponential increase in volume of remote sensing data, which has pushed the need for intelligent automation of data extraction for wildfire studies. Machine learning offers accurate automation in detecting such natural anomalies and enable decision-makers to take actions in a timely manner. Recent advances in machine learning algorithms, namely probabilistic generative methods, allow researchers and decisionmakers to step beyond detection and study “what-if” scenarios for wildfire occurrences. Additionally, they offer better imitations to the stochastic behavior of nature, and wildfire events. However, optimizing the performance of these probabilistic generative models is a computationally expensive process, specially using digital computers. On the other hand, quantum computers have recently shown a promise to reduce computationally costly training of such models and provide performance improvements. There is a body of research investigating the potential for improved machine learning methods in which key operations are performed on a quantum computer. In this study, we propose a probabilistic image-toimage segmentation approach combining a very well-known segmentation method, U-NET, with a Conditional Variational Auto-Encoder (CVAE) to not only detect wildfires but also describe the stochasticity of the phenomenon and be capable of running “what-if” scenarios. Our proposed model is compatible with training on quantum computers, which results in a quantum-assisted image-to-image segmentation approach and can be used to benchmark the potential benefit of quantum computing over the classical one.

quantum↗
DOE OSTI2022

Robust Scheduling of Microgrids Considering Unintentional Islanding Conditions

This paper proposes a robust scheduling model for microgrids considering the stochastic unintentional islanding conditions. The proposed model minimizes the total operating cost of the microgrid by efficiently coordinating the supply of power from local distributed energy resources and the main grid. To capture the prevailing uncertainties in renewable generation and demand as well as unintentional islanding conditions, a two-stage adaptive robust optimization model is formulated to minimize the total operating cost under the worst realization of the modeled uncertainties. The column and constraint generation (C&CG) method is used to solve the problem in an iterative manner. The solution of the proposed scheduling model ensures robust microgrid operation in consideration of all possible realization of renewable generation, demand and unintentional islanding condition. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, two micro-turbines, a diesel generator and a battery demonstrate the effectiveness of the proposed approach.

Liu, Guodong↗
NASA NTRS1983

Study for analysis of benefit versus cost of low thrust propulsion system

The benefits and costs associated with placing large space systems (LSS) in operational orbits were investigated, and a flexible computer model for analyzing these benefits and costs was developed. A mission model for LSS was identified that included both NASA/Commercial and DOD missions. This model included a total of 68 STS launches for the NASA/Commercial missions and 202 launches for the DOD missions. The mission catalog was of sufficient depth to define the structure type, mass and acceleration limits of each LSS. Conceptual primary propulsion stages (PPS) designs for orbital transfer were developed for three low thrust LO2/LH2 engines baselined for the study. The performance characteristics for each of these PPS was compared to the LSS mission catalog to create a mission capture. The costs involved in placing the LSS in their operational orbits were identified. The two primary costs were that of the PPS and of the STS launch. The cost of the LSS was not included as it is not a function of the PPS performance. The basic relationships and algorithms that could be used to describe the costs were established. The benefit criteria for the mission model were also defined. These included mission capture, reliability, technical risk, development time, and growth potential. Rating guidelines were established for each parameter. For flexibility, each parameter is assigned a weighting factor.

Hamlyn, K. M.↗
DOE OSTI2022

A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it. These processes are considered, to start from the aortic inlet to the capillaries and tissue of the breast. Large variations in biophysical properties and flow conditions exist in this system necessitating the use of different flow models for different geometries and flow regimes. In total, we consider four different model types. First, a system of 1D nonlinear hyperbolic partial differential equations (PDEs) is considered to simulate blood flow in larger arteries with highly elastic vessel walls. Second, we assign 1D linearized hyperbolic PDEs to model the smaller arteries with stiffer vessel walls. The third model type consists of ODE systems (0D models). It is used to model the arterioles and peripheral circulation. Finally, homogenized 3D porous media models are considered to simulate flow and transport in capillaries and tissue within the breast volume. Sink terms are used to account for the influence of the venous and lymphatic systems. Combining the four model types, we obtain two different 1D–0D–3D coupled models for simulating blood flow and transport processes: The first model results in a fully coupled 1D–0D–3D model covering the complete path from the aorta to the breast combining a generic arterial network with a patient specific breast network and geometry. The second model is a reduced one based on the separation of the generic and patient specific parts. The information from a calibrated fully coupled model is used as inflow condition for the patient specific sub-model allowing a significant computational cost reduction. Several numerical experiments are conducted to calibrate the generic model parameters and to demonstrate realistic flow simulations compared to existing data on blood flow in the human breast and vascular system. Moreover, we use two different breast vasculature and tissue data sets to illustrate the robustness of our reduced sub-model approach.

multiscale blood flow models↗
DOE OSTI2021

Extended convex hull-based distributed optimal energy flow of integrated electricity-gas systems

Integrated electricity and gas systems are constructed to facilitate the gas-fired generation, and the distributed operation of these integrated systems have received much attention due to the increased emphasis on data security and privacy between different agencies. This paper proposes an extended convex hull based method to address optimal energy flow problems for the integrated electricity and gas systems in a distributed manner. First, a multi-block electricity-gas system model is constructed by dividing the whole system into N blocks considering both physical and regional differences. This multi-block model is then convexified by replacing the nonconvex gas transmission equation with the extended convex hull-based constraints. The Jacobi-Proximal alternating direction method of multipliers algorithm is adopted to solve the convexified model and minimize its operation cost. Finally, the feasibility of the optimal solution for the convexified model is checked, and a sufficient condition is developed. If the sufficient condition is satisfied, the optimal solution for the original nonconvex problem can be recovered from that for the convexified problem. Simulation results demonstrate that the proposed method is tractable and effective in obtaining feasible optimal solutions for multi-block optimal energy flow problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗