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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MARS: Malleable Actor-Critic Reinforcement Learning Scheduler

In this paper, we introduce MARS, a new scheduling system for HPC-cloud infrastructures based on a cost-aware, flexible reinforcement learning approach, which serves as an intermediate layer for next generation HPC-cloud resource manager. MARS ensembles the pre-trained models from heuristic workloads and decides on the most cost-effective strategy for optimization. A whole workflow application would be split into several optimizable dependent sub-tasks, then based on the pre- defined resource management plan, a reward will be generated after executing a scheduled task. Lastly, MARS updates the Deep Neural Network (DNN) model based on the reward. MARS is designed to optimize the existing models through reinforcement mechanisms. MARS adapts to the dynamics of workflow applications, selects the most cost-effective scheduling solution among pre-built scheduling strategies (backfilling, SJF, etc.) and self- learning deep neural network model at run-time. We evaluate MARS with different real-world workflow traces. MARS can achieve 5%-60% increased performance compare to state-of-the- art approaches.

Baheri, Betis↗
NASA NTRS2004

Guidelines for Developing Spacecraft Structural Requirements: A Thermal and Environmental Perspective

Spacecraft are typically designed with a primary focus on weight in order to meet launch vehicle performance parameters. However, for pressurized and/or man-rated spacecraft, it is also necessary to have an understanding of the vehicle operating environments to properly size the pressure vessel. Proper sizing of the pressure vessel requires an understanding of the space vehicle's life cycle and compares the physical design optimization (weight and launch "cost") to downstream operational complexity and total life cycle cost. This paper will provide an overview of some major environmental design drivers and provide examples for calculating the optimal design pressure versus a selected set of design parameters related to thermal and environmental perspectives. In addition, this paper will provide a generic set of cracking pressures for both positive and negative pressure relief valves that encompasses worst case environmental effects for a variety of launch / landing sites. Finally, several examples are included to highlight pressure relief set points and vehicle weight impacts for a selected set of orbital missions.

Holladay, Jon↗
DOE OSTI2022

An optimization framework for the network design of advanced district thermal energy systems

In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, "What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?" A particle swarm optimization approach is validated to address the selection of the subset of buildings, and a graph theory-based heuristic is validated for selection of the network topology for any candidate subset of buildings. The framework is applied to a prototypical urban district for illustrative purposes. Additionally, modeling of prototypical districts revealed reductions in source energy use intensity for heating and cooling of 21-25% through the use of advanced district energy systems relative to code-compliant, building level systems. The framework identifies solutions with life cycle cost values 14% to 72% lower than that of base case scenarios based on conventional design approaches, depending on the base case scenario selected. Analysis of the search space indicates that topology optimization facilitates reductions in life cycle cost, source energy use intensity, and carbon emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Levelized cost of charging of extreme fast charging with stationary LMO/LTO batteries

Extreme DC fast charging for electric vehicles (EVs) could be competitive with the internal combustion engine refueling experience and enable longer-distance travel, which could help with EV adoption and decarbonization, but these systems have high capital costs and extremely variable high-power demands. Behind-the-meter systems (BTMS) could support extreme-fast-charging (XFC) stations to increase nationwide adoption of EVs. Here, this study examines the optimal break-even levelized cost of charging (LCOC) across 96 BTMS scenarios to enable low-wait XFC stations providing 200 miles of charge in 10 min. This research simulates LCOC via synthetic XFC-capable EV loads, machine-learned battery life models from testing data, and nonlinear optimal controls, co-minimizing complex utility costs and battery replacements. An aggregate optimal BTMS design treating each EV load as equal likely gives an optimal LCOC per utility rate, the average of which is $\$$0.59/kWh. In addition, the sensitivity of optimal and off-optimal design factors, the long-life LMO/LTO chemistry, and optimized controls are analyzed. The battery control model, based on battery stressors to compare chemistries, optimizes LMO/LTO resting state of charge and cycle depth without compromising cost reduction, which enables greater flexibility in operation. The LCOC savings due to replacement reduction are small, up to $\$$0.035/kWh (6%), with an average of $\$$0.02/kWh (3.5%). Compared with gasoline stations, the aggregate XFC station design achieves comparable speed, experience of service, and cost at $\$$3.81/gal gasoline, showing that EVs can replace gasoline vehicles even for longer-distance travel.

25 ENERGY STORAGE↗
DOE OSTI2022

Seamlessly Fuel Flexible Heat Pump with Optimal Model-based Control Strategies to Reduce Peak Demand, Utility Cost and CO2 Emission

This research develops a novel hybrid fuel heat pump system for space heating of residential and small commercial buildings with built-in optimization and control. Whereas conventional dual fuel systems either run on gas or electricity at any given moment, the proposed seamlessly fuel flexible heat pump (SFFHP) simultaneously consumes gas and electricity and continuously optimizes the proportion of each. The building air flows across the heat pump condenser first and then flows across the furnace coil, and this reduces the heat pump temperature lift. The SFFHP delivers energy savings by allowing each subsystem (gas furnace and electric heat pump) to operate where it performs best to improve energy efficiency, minimize energy cost, and minimize carbon footprint. The capacities of the electric heat pump and gas furnace are continuously adjusted based on ambient conditions, utility price signals, and marginal grid emission signals. An optimal model predictive control strategy was developed with the goal of minimizing utility cost and minimizing CO2 emission. Two case studies were conducted to simulate the performance of SFFHP during the heating season in Chicago and Los Angeles, respectively. Compared with a conventional electric heat pump, SFFHP yields 33% utility cost reduction and 49% CO2 emission reduction in Chicago. Similarly, it achieves 23% utility cost reduction and 17% CO2 emission reduction in Los Angeles. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. Due to the hybrid fuel nature of this novel equipment, user comfort will always be maintained. The fuel flexibility makes it an attractive option for demand response programs.

Li, Zhenning↗
DOE OSTI2022

SolarPlus-Optimizer v0.1

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this software package, we present the "Solar+ Optimizer" (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

Prakash, AnandKrishnan↗
DOE OSTI2025

Learning from Arctic Microgrids: Cost and Resiliency Projections for Renewable Energy Expansion with Hydrogen and Battery Storage

Electricity in rural Alaska is provided by more than 200 standalone microgrid systems powered predominantly by diesel generators. Incorporating renewable energy generation and storage to these systems can reduce their reliance on costly imported fuel and improve sustainability; however, uncertainty remains about optimal grid architectures to minimize cost, including how and when to incorporate long-duration energy storage. This study implements a novel, multi-pronged approach to assess the techno-economic feasibility of future energy pathways in the community of Kotzebue, which has already successfully deployed solar photovoltaics, wind turbines, and battery storage systems. Using real community load, resource, and generation data, we develop a series of comparison models using the HOMER Pro software tool to evaluate microgrid architectures to meet over 90% of the annual community electricity demand with renewable generation, considering both battery and hydrogen energy storage. We find that near-term planned capacity expansions in the community could enable over 50% renewable generation and reduce the total cost of energy. Additional build-outs to reach 75% renewable generation are shown to be competitive with current costs, but further capacity expansion is not currently economical. We additionally include a cost sensitivity analysis and a storage capacity sizing assessment that suggest hydrogen storage may be economically viable if battery costs increase, but large-scale seasonal storage via hydrogen is currently unlikely to be cost-effective nor practical for the region considered. While these findings are based on data and community priorities in Kotzebue, we expect this approach to be relevant to many communities in the Arctic and Sub-Arctic regions working to improve energy reliability, sustainability, and security.

25 ENERGY STORAGE↗
NASA NTRS1975

A study of low cost approaches to scientific experiment implementation for shuttle launched and serviced automated spacecraft

Cost reductions that can be obtained in experiment instrumentation by the use of standardized electronics and by the relaxation of instrument reliability requirements are studied. The feasibility of using standardized equipment for experiment instrumentation is assessed and a system design approach that most effectively incorporates standardized equipment is developed. The level and form of modularization that is appropriate for the standardized equipment is determined. Mission assurance aspects of instrument development are examined to determine the cost reductions that might be derived from the relaxation of reliability requirements and to formulate a systematic approach to the optimization of mission assurance cost reductions. The results of the analyses are applied to a representative model HEAO payload in order to provide a concrete example of the cost reductions that can be achieved by a standardized approach to the instrument electronics.

Source record↗
DOE OSTI2022

Real-Time Drilling Optimization System for Improved Overall Rate of Penetration and Reduced Cost Per Foot in Geothermal Drilling

The key to success in geothermal drilling is economic feasibility, and a major cost in the development of geothermal resources is the actual drilling of the wells. In this project, a real-time drilling optimization system for geothermal drilling was developed. The system couples three individual components while drilling. The first component is a drill stem vibration analysis model, the second is Mechanical Specific Energy (MSE) analyses, and the third is a detailed PDC Rate of Penetration (ROP) drill bit model for optimum RPM and WOB combinations. The benefit of the coupled system is that the range of WOB and RPM could be selected to avoid drill stem vibrations. Secondly, MSE is used as an efficiency measure and the detailed PDC drill bit model ensures the drill bit does not endure temperatures that exceed the temperature at which the PDC cutters experience accelerated wear. The new detailed PDC bit model is based on rock/bit interaction that physically tracks the PDC cutter wear flats as the bit drills ahead giving the capability to calculate the temperature being generated underneath the worn cutters to better advise on operational parameters to avoid accelerated cutter wear and failure and to ensure that operational parameters are applied so that overall ROP is maximized. By combining the drill stem vibrations and the detailed PDC bit cutter wear and “safe” non-accelerated cutter wear temperature and optimum ranges of operating parameters, it results in higher ROP and lower cost drilling. Single cutter PDC testing performed in different lithologies at Sandia was utilized to verify the PDC cutter forces and depth of cut for new and worn cutters. Based on single cutter PDC temperature modeling, verification using single cutter data from the testing done by National Oilwell Varco (NOV) was performed. Sandia’s Hard-Rock Drilling Facility (HRDF) was utilized to test different drill bit configurations with different cutter designs and wear status with different induced modes of vibration to obtain the critical bit RPM/WOB ranges resulting in ineffective drilling and low ROP. The collected test data were further used to verify and calibrate the full hole PDC ROP model that was developed based on single cutter interaction data. A full coupled drill stem vibration model was formulated and verified with geothermal field data from the Chocolate Mountain Aerial Gunnery Range (CMAGR). A graphical user interface (GUI) was developed using Tkinter library in the computer programming language Python, which integrates all the developed models in one system. The developed system consists mainly of the PDC ROP model, PDC bit wear model, PDC cutter temperature model, Mechanical Specific Energy (MSE) model, and drillstring vibration model integrated into one system. The developed system can be used for both, post well analysis and real-time optimization using different criteria such as ROP maximization or MSE minimization. The software uses Differential Evolution Algorithm (DEA) to find optimum values for operational parameters based on last foot drilled while avoiding the drillstring vibration and cutter temperature critical operating parameters.

15 GEOTHERMAL ENERGY↗
NASA NTRS1971

The Apollo Lunar Roving Vehicle.

After listing the basic requirements such as operational demands and lunar environmental conditions, characteristic design data of the roving vehicle are given with special attention to the four wheel drive and its control system, the steering system, and the navigational instrumentation. The overall system is optimized in view of total mass, range, mobility, load carrying capability, safety, highest reliability through redundancy, and last but not least, cost and development time. Optimization of the drive and power system has first been evaluated by mathematical models and computational simulation of the vehicle hardware, the wheel/soil interaction, and the lunar terrain profile. The next step to refine optimization and evaluation of the drive, steering, and power system including man/machine interaction has been carried out by the use of a six-degree-of-freedom simulator subjecting the astronauts in their space suits to simulated vehicle motions while driving over a simulated terrain, observable on a cathode ray tube display.

Haeussermann, W.↗
NASA NTRS1983

A study of altitude and flight path angle dynamics for a singularly perturbed fuel optimization problem

This short paper will demonstrate that the separation of altitude and flight path angle dynamics using singular perturbation techniques for a transport fuel optimization problem results in an unacceptable oscillation in altitude. A technique for damping this oscillation by adding a penalty term to the cost function for the optimization problem will be discussed. This technique will be compared with a different approach that linearizes the altitude and flight path angle boundary layers.

Price, D. B.↗
NASA NTRS2012

On Optimal Control of Non-Autonomous Switched Systems with a Fixed Mode Sequence

We consider differentiability with respect to the switch times of the value function of an optimal control problem for a non-autonomous switched system. The control variables are the switch times between the modes and the input in each mode. We provide a method to compute the derivative of the cost function given a nominal input. Then, we view the optimal control problem as a parametrized optimization problem in which the switch times are the parameters and the optimization is over the set of feasible inputs of each mode. From this point of view, we provide conditions under which the continuity and differentiability of the optimal value function, that is the cost function optimized over the inputs, can be guaranteed.

Kamgarpour, Maryam↗
DOE OSTI2026

Carbon fiber design improvements based on economic models

Circular fiber geometries are predominant in commercial carbon fiber material systems, but the use of this fiber shape has numerous limitations. Circular geometries have continuous symmetry, which is helpful for various processing considerations, but also have the largest possible maximum diffusion thickness for a given fiber area. This characteristic means that circular carbon fibers always have the highest material processing cost and lowest production throughput compared to any other fiber shape with the same area and tow count. To quantify material cost and other benefits for non-circular carbon fiber geometries, process models for polyacrylonitrile based carbon fiber production are developed in relationship to the carbon fiber shape, size, and tow count. For a given fiber shape, precursor production costs are shown to favor maximizing fiber size while conversion costs are minimized by the smallest fiber size. These competing cost trends result in a numerically optimal fiber size for a given shape and tow count, while both cost components are decreased by increasing tow count. Cost–performance tradeoffs for three lobe fiber geometries are studied by supplementing the cost trends with a numerical failure model to predict compressive strength for discrete shape variants. The shape selection is shown to be more sensitive to variations in cost than compressive strength while suboptimal shape designs can improve manufacturing robustness and achievable fiber volume fractions. Finally, an optimal three lobe carbon fiber is identified that balances the set of considerations while reducing costs and embodied energy and increasing production throughput compared to a commercial carbon fiber.

Carbon fiber↗
DOE OSTI2021

A Fundamental Economic Assessment of Recovering Rare Earth Elements and Critical Minerals from Acid Mine Drainage Using a Network Sourcing Strategy

In recent years, acid mine drainage (AMD) has emerged as a promising unconventional source of rare earth elements (REEs) and other critical minerals (CMs) such as cobalt and manganese. In this regard, AMD provides a natural heap leaching effect that extracts and concentrates REE/CM from the host strata creating a partially enriched feedstock suitable for downstream extraction, separation, and recovery. While several prior studies have described processes and approaches for the valorization of AMD, very few have described the supply chain and infrastructure requirements as well as the associated economic assessment. To that end, this paper provides a fundamental economic assessment of REE/CM recovery from AMD using a network sourcing strategy in addition to a robust, flexible feedstock separations and refining facility. The methodology of this paper follows that of a typical techno-economic analysis with capital and operating costs estimated using AACE Class IV (FEL-2) guidelines. To demonstrate the range of possible outcomes, four pricing scenarios were modeled including contemporary prices (September, 2021) as well as the minimum and maximum prices over the last decade. In addition, five production scenarios were considered reflecting variations in the product suite, ranging from full elemental separation to magnet REE and CM production only (i.e., Pr, Nd, Tb, Dy, Y, Sc, Co, and Mn). The results of this analysis show that, with the exception of the minimum price scenario, all operational configurations have positive economic indicators with rates of return varying from 25% to 32% for the contemporary price scenario. The optimal configuration was determined to be production of Co, Mn, and all REEs except for mischmetal, which is not recovered. Sensitivity analysis and Monte Carlo simulation show that capital cost and HCl consumption are the two major factors influencing rate of return, thus indicating opportunities for future technology development and cost optimization. Implications of the study and a cooperative profit-sharing model for sourcing are also described.

42 ENGINEERING↗
DOE OSTI2024

Economically Viable Intermediate to Long Duration Hydrogen Energy Storage Solutions for Fossil Fueled Assets

This report was prepared as an account of work sponsored by the Office of Fossil Energy and Carbon Management of U.S. Department of Energy under Funding Opportunity Announcement Number DE-FOA-0002332 “Energy Storage for Fossil Power Generation”. The work aimed to explore and advance an innovative hydrogen energy storage system – the synergistically integrated hydrogen energy storage system (SIHES) – that has the following characteristics: • Compatible with existing or new coal and gas fuel electricity generation units, • best suited for intermediate to long duration energy storage, from 12 hours to weeks even months, and • capable of storing energy at the utility scale – hundreds of MWh to GWh energy storage with power output level in tens to hundreds of MW. Preliminary front-end engineering design (Pre-FEED) studies was carried out to develop and refine a site-specific SIHES as peaking power generation units (so named as HyPeaker) as the first market entry point, to demonstrate both the technical feasibility and the economic viability to integrate the HyPeaker “within the fence” of a fossil power plant. This specific site was TVA’s Johnsonville Combustion Turbine Plant. The HyPeaker was designed and engineered to integrate with a 60MW aeroderivative gas turbine unit already available at TVA’s Johnsonville site. This site-specific HyPeaker consists of an alkaline electrolyzer to produce hydrogen from CO 2 free electricity sources, an innovative low-cost high-pressure hydrogen storage system (Big-Ton) and the aero gas turbine to generate electricity using blend of hydrogen and natural gas. A holistic system level technoeconomic analysis tool specific to HyPeaker was developed to optimize the engineering design of the Johnsonville site-specific HyPeaker for cost and performance. The optimal design and specification of the Johnsonville site-specific HyPeaker are the following: • Alkaline electrolyzer: 3MW • Big-Ton storage vessel: 11,000kg H 2 at 3000psi. • 4-stage diaphragm hydrogen compressor: 55kg-H 2 /hr from 150psi to 3000psi. The HyPeaker is designed to provide sufficient hydrogen for 90% continuous operation of the HyPeaker. All major components have design life of 30 years. The capex of HyPeaker is estimated at $\$$7.1M. This included $\$$1.5M for the electrolyzer, $\$$5.6M for the storage vessel and compressor. The cost of aero gas turbine was included as it is already available at the site. Key findings are: • HyPeaker can be designed, manufactured, installed and integrated with the fossil power plants, with sub-systems and components commercially available on the market today, even when it is scaled up to an order of magnitude larger than the one at the Johnsonville site. HyPeaker is a technologically viable solution to cover a wide range of energy storage duration needs, from daily peaking operation to seasonal shifting for fossil fueled assets. • The cost advantage of SCCV based Big-Ton H 2 storage vessel made it possible to “oversize” the H 2 storage subsystem to achieve overall system level cost optimization. The benefits are two-fold. First, it allows to significantly reduce the capacity and cost of electrolyzer by spreading H 2 production over a much longer period of time when the fuel cost for electricity production is low. Second, it allows to balance the hydrogen production and usage shift over weeks to months to meet the peak demands. As such, the capital cost of HyPeaker system using the Big-Ton was less than half of the cost of a system with today’s steel tube based H 2 storage system. The HyPeaker has even better cost advantage Li-ion battery based energy storage system. The estimated capital cost of Li-Ion battery system would be at $\$$38M, under the same projected 20-year electricity generation profile of the Johnsonville site. This is over 5 times more expensive than the HyPeaker system. • Since industry scale energy storage systems do not have 100% energy conversion and storage efficiency, energy storage systems using fossil fuel generated electricity would increase the CO 2 emission. This is particularly the case for HyPeaker due to its low round trip efficiency. Therefore, a more sensible solution would be to the excessive or curtailed electricity from CO 2 emission free sources such as solar farms, wind farms or nuclear power plants, to produce hydrogen, and integrate them with the HyPeaker. Electricity from TVA’s nuclear power plants was used for the Johnsonville HyPeaker. • The economic viability of HyPeaker is expected to be further improved when global supply chains are taken into consideration. For the same Johnsonville site specific HyPeaker, the capex would be reduced to ~$\$$3.6M from ~$\$$7.1M, and the added LCOE is reduced to ~$\$$85/MWh. With the bipartisan Infrastructure Investment and Jobs Act, the cost of domestically produced HyPeaker sub-systems would be at the level of today’s global suppliers. Since the peaking units generally operate at peak usage period, thereby demanding higher price, the projected $\$$85/MWh LCOE would be within the realm of financial viability for utility operators.

08 HYDROGEN↗
DOE OSTI2022

A method for determining optimal electric range by considering electric vehicle lightweighting on perceived ownership cost

The limited driving range due to high costs and low energy densities of batteries constraints the battery electric vehicle (BEV) market growth. Lightweighting in theory can reduce energy consumption rate and extend the driving range. The knowledge gap is to quantitatively link the cost-effectiveness of light-weight technologies with range extension and consumer acceptance of BEVs. In this study, a physics-based energy consumption model of BEVs is constructed and associated with a statistics-based model on the basis of travel surveys. A perceived cost of ownership (PCO) is then developed by adding intangible costs to traditional total cost of ownership models. We estimate, at the disaggregate vehicle model and driver level and the aggregate market level, 1) the extended range due to lightweighting for a given battery size; and 2) the optimal electric range based on lightweighting decisions. The cost-effectiveness of lightweighting for BEV range extension is found to vary with income-dependent daily range limitation value, driving patterns and lightweighting technology costs. In general, adopting lightweighting in BEVs is more cost-effective for consumers with higher daily limitation value, as well as for those with higher driving intensity or suitable daily driving patterns. When the lightweighting involves a higher vehicle production cost, less lightweighting could reduce the overall PCO for BEV owners. 4 of the selected top ten BEV models are found to benefit from additional 2.09%–4.45% lightweighting. Finally, the method built in this study can guide automakers in planning R&D investments in battery and lightweighting technologies.

33 ADVANCED PROPULSION SYSTEMS↗