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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Conducting Feasibility Studies in a Virtual World: Lessons Learned and Emerging Best Practices from the NASA DEVELOP Program

In response to new workplace realities, the NASA DEVELOP National Program pivoted from co-locating students, emerging professionals, and science advisors to bringing together virtual teams from across the United States. In its spring 2020 term, rapidly evolving circumstances required an ad-hoc roll-out of a virtual approach to complete the spring projects. Based on the experience from the spring term and a few weeks of planning, DEVELOP then conducted a fully virtual summer term with features such as 1) online collaboration tools, 2) virtual machines for analysis, and 3) streamed training offerings, including DEVELOP’s first ever program-wide Software Carpentry workshop. This full term of bringing together remote actors to select, build, and manage teams brought many challenges. Summer feedback has influenced planning for the fall 2020 term and process improvement is ongoing. This presentation will highlight lessons learned throughout this period of rapid change. Feedback from spring and summer terms and the Software Carpentry workshop will be summarized. Beyond participant impacts, there will also be discussion of effects on project results and partner experience. Final takeaways will focus on best practices that have been distilled for virtually-conducted feasibility studies.

NASA DEVELOP↗
NASA NTRS2022

Validation of a High-Fidelity Supersonic Parachute Inflation Dynamics Model and Best Practice

The parachute inflation dynamics (PID) of a Disk-Gap-Band (DGB) parachute system travelling at supersonic velocities in the high-altitude Earth atmosphere is simulated using a high-fidelity, multiphysics, massively-parallel computational framework. The sensitivity of the simulation results with respect to critical modelling and simulation parameters, including the fluid mechanical governing equations (Euler vs Navier-Stokes with RANS turbulence closure vs Navier-Stokes with LES turbulence closer), the interaction between the flow and the suspension lines (accounted for vs not accounted for), the dynamics of the payload (restrained vs free), and the material model of the heterogeneous fabric canopy (Saint-Venant Kirchoff vs mechanics-informed multiscale neural network), is extensively investigated. The parameter investigation is enabled by advancements to the state-of-the-art in the modelling and simulation of the supersonic parachute inflation process, which are presented as part of the computational framework. The predictive quality of the computational framework in the context of supersonic PID is validated by comparison of the simulation results with the experimental results from NASA’s Advanced Supersonic Parachute Research (ASPIRE) project. Through the validation, best practices for the modelling and simulation of supersonic PID are developed and proposed.

Rabinovitch, Jason↗
DOE OSTI2023

Geothermal Play Fairway Analysis Best Practices

Play fairway analysis (PFA) is a methodology that can improve success rates for geothermal exploration drilling, thus reducing the costs of geothermal projects while facilitating development in new areas. It was originally developed for the oil and gas industry, but has been adapted for discovering geothermal resources over the last decade. The geothermal PFA methodology involves systematically screening a set geographic area for promising qualities typically related to the presence of heat, permeability, and fluid. Successful application of PFA can identify hidden hydrothermal systems. From 2014 to 2021 the U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) supported the development of PFA for geothermal resources through awards to 11 research teams across the country. The goal of these projects was to advance and adapt PFA for geothermal exploration to produce regional-scale maps that reduce exploration uncertainty. This report is an outcome of the NREL-led PFA Retrospective project, which compiled, synthesized, analyzed the results of GTO's geothermal PFA program. Ultimately, we find that these projects greatly advanced approaches to geothermal exploration and resulted in extensive new data and new discoveries of unrecognized geothermal systems. We used the results to distill best practices in this report and to provide guidance for future applications of geothermal PFA.

15 GEOTHERMAL ENERGY↗
NASA NTRS2021

From Low-Cost Sensors to High-Quality Data: A Review of Challenges and Summary of Best Practices for Effectively Using Low-Cost Particulate Matter Mass Sensors

Low-cost sensors for particulate matter mass (PM) enable spatially dense, high temporal resolution measurements of air quality that traditional reference monitoring cannot. Low-cost PM sensors are especially beneficial in low and middle-income countries where few, if any, reference grade measurements exist and in areas where the concentration fields of air pollutants have significant spatial gradients. Unfortunately, low-cost PM sensors also come with a number of challenges that must be addressed if their data products are to be used for anything more than a qualitative characterization of air quality. The various PM sensors used in low-cost monitors are all subject to biases and calibration dependencies, corrections for which range from relatively straightforward(e.g. meteorology, age of sensor) to complex (e.g. aerosol source, composition, refractive index). The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. We also present a set of best practices to follow to obtain high-quality data from these low-cost sensors.

low-cost sensors↗
DOE OSTI2026

Best Practices for Regulatory Engagement and Relationship Building – 26129

In the initiation of a new project or facility, the management team should begin to engage with appropriate regulators, early and often. However, if this did not occur and new issues arise, new challenges develop, or regulatory impacts become a concern, the regulatory engagement process should be reconsidered and reevaluated. Regulators are key in the siting, construction, and continued operations of a new facility. Municipalities often seek to attract new initiatives, projects, or facilities that will have a significant positive impact on the community. Even though this is typically the goal, there are many hurdles along the path that may cause negative impacts leading to regulatory concerns and hurdles that may delay or stop work. Additionally, early and frequent engagement with regulators can have a significant positive impact on the successful siting, permitting, and construction of a facility, including meeting needed schedules that are important to economic viability. Further, it is essential for ongoing operations for regulators to be effectively and meaningfully engaged throughout the life of the project or facility due to the potential of changing factors during the construction and/or operation. Regular and consistent engagement builds relationships and helps ensure that potential topics of concern are addressed early before they become problems. In this paper, we will discuss best practices in engaging with regulators, how to initiate effective regulatory interactions, and building lasting relationships.

Jacobs, Stephanie [Savannah River National Laborat↗
DOE OSTI2026

Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices

Climate model simulations are an important source of information about our planet’s climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space–time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation.

Climate models↗
DOE OSTI2021

Best Practices Guide: Benchmarking Energy Efficiency in Laboratories

Purpose and Audience A wide spectrum of laboratory owners, ranging from universities to federal agencies, have explicit goals for energy efficiency and greenhouse gas reductions in their facilities. For example, new federal buildings and major renovations of existing buildings are to reduce fossil fuel-generated energy consumption by 90% in 2025, and 100% in 2030, compared with a 2003 baseline (FEMP n.d.). Minnesota SB2030 standard requires achieving an 80% reduction from the average building baseline for commercial, institutional, and industrial buildings (SB2030 n.d). A laboratory—new or existing—is much more likely to meet energy efficiency goals if quantitative metrics and targets are explicitly specified and tracked over the life cycle of the building, from design through construction, commissioning, operations, and renovations. If efficiency targets are not explicitly and properly defined, any additional capital costs or design time associated with attaining higher efficiencies can be difficult to justify relative to other priorities. The purpose of this guide is to provide guidance on how to specify and compute energy efficiency metrics and benchmarks for laboratories, at the whole-building as well as the system level. The information in this guide can be used to incorporate quantitative metrics and targets into new construction or retrofit of existing facilities. For information on strategies and technologies to achieve energy efficiency, the reader is referred to I2SL resources, including technology best practice guides and case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Energy Master Planning for Resilient Public Communities—Best Practices from U.S. Military Installations

Until recently, most planners at military installations addressed energy systems for new facilities on an individual facility basis without consideration of community-wide goals relevant to energy sources, renewables, storage, or future energy generation needs. Building retrofits of public buildings typically do not address energy needs beyond the minimum code requirements making it difficult, if not impossible, to achieve community-level targets on a building-by-building basis. Planning on the basis of cost and general reliability may also fail to deliver community-level resilience. For example, many building code requirements focus on hardening to specific threats, but in a multi-building community, only a few of these buildings may be mission-critical. Over the past two decades, the frequency and duration of regional power outages and water utility disruptions from weather, man-made events, and aging infrastructure have increased. Major disruptions of electric and thermal energy have degraded critical mission capabilities and caused significant economic impacts. In 2016, the U.S. Department of Defense issued guidance that each Service (Army, Navy, Air Force, Marines) complete comprehensive energy plans for the installations that consumed 75% of total building energy. Guidance was updated in 2017 to include metrics for energy resilience, and in some cases, water. This paper describes how community level quantitative and qualitative resilience analysis and metrics have been incorporated into community energy and water planning best practices for military installations in three geographically diverse locations. It is based on research performed under the International Energy Agency’s “Energy in Buildings and Communities Program Annex 73,” focusing on development of guidelines and tools that support the planning of Net Zero Energy Resilient Public Communities as well as research performed under the Department of Defense Environmental Security Technology Certification Program project EW18-D1- 5281, “Technologies Integration to Achieve Resilient, Low- Energy Military Installations.” The first case study reviews progress made on an energy and water planning study conducted at Fort Bliss, Texas. The second and third describes planning conducted at Fort Bragg, North Carolina and the Joint Region Marianas, Guam, respectively, under the updated guidance from 2017 regarding energy and water resilience. Analysis methods, key metrics, and key infrastructure and operational constraints are described, as well as technical, economic and business concepts used during the planning process.

Urban, Angela B.↗
DOE OSTI2024

Polymer Additive Manufacturing for Marine Renewable Energy Applications: Best Practices, Research Trends, and Current Challenges

Additive manufacturing (AM) is a rapidly growing technology space, not only for prototyping, but is also becoming more feasible at larger scales and increasing component quantities. There are a large variety of AM processes and materials available to users and effectively applying those processes and materials to a specific use case can be challenging. One specific area where AM could be particularly beneficial is marine renewable energy (MRE). Not only is MRE a relatively nascent industry with a near-term need for rapid deployments and prototype testing, but developers could also see long-term benefits from the broad variety of environmentally resistant materials available and the ability to manufacture complex geometries that AM technologies offer. Over the past 4 years, AM materials have played an increasing role in the Advanced Materials project; a multi-year, multi-laboratory research project funded by the U.S. Department of Energy's Water Power Technologies Office, with the main goal of reducing barriers to the adoption of complex materials in the MRE industry. The primary focus of this project is to develop test methods and generate datasets to understand the long-term performance of advanced materials in marine environmental and address specific material challenges as they arise. This report provides an extensive overview of the research that has been performed specific to AM polymers as part of the Advanced Materials project. The intention of this document is to provide recommendations of best practices with regards to material selection, mechanical test method development, and design practices, lessons learned along the way, current research trends, and ongoing challenges with regards to AM polymers in marine environments. In particular, this report focuses on several key aspects: Material and process selection, Environmental conditioning and subsequent degradation quantification through mechanical characterization, Composite reinforcements on AM polymer substrates, Adhesion of instrumentation for mechanical characterization and loads measurements, Protective coatings for preventing biofouling and water ingress, Other MRE case studies where AM has proved particularly useful. Ultimately, we hope that the test methods that have been developed, data generated, and lessons learned from this research will be valuable to the MRE community (researchers and developers alike), as well as other industries, and can be used as a reference point as the respective MRE and AM industries continue to grow and mature.

16 TIDAL AND WAVE POWER↗
NASA NTRSDate not supplied

Satellite Conjunction Assessment, Risk Analysis and Collision Avoidance Best Practices: The History, Evolution and Opportunities

Since Explorer 1 was launched on January 31, 1958, the United States (U.S.) has reaped the benefits of space exploration. New markets and new technologies have spurred the economy and changed lives in many ways across the national security, civil, and commercial sectors. Space technologies and space-based capabilities now provide global communications, navigation and timing, weather forecasting, and more. Space exploration also presents challenges that impact not only the U.S. but also its allies and other partners. A significant increase in the volume and diversity of activity in space means that it is becoming increasingly congested. Emerging commercial ventures such as satellite servicing, in-space manufacturing, and tourism as well as new technologies enabling small satellites and large constellations of satellites present serious challenges for safely and responsibly using space in a stable, sustainable manner. To meet these challenges, the U.S. seeks to improve global awareness of activity in space by publicly sharing flight safety-related information and by coordinating its own on-orbit activity in a safer, more responsible manner. It seeks to bolster stability and reduce current and future operational on-orbit risks so that space is sustained for future generations. To this end, new and better Space Situational Awareness (SSA) capabilities are needed to keep pace with the increased congestion, and the U.S. seeks to create a dynamic environment that encourages and rewards commercial providers who improve these capabilities. The National Aeronautics and Space Administration (NASA) Spacecraft Conjunction Assessment and Collision Avoidance Best Practices Handbook reflects how NASA currently operates, which has evolved over time. Consideration is given to important topics such as spacecraft and constellation design; spacecraft “trackability;” pre-launch preparation and early launch activities; on-orbit collision avoidance; and automated trajectory guidance and maneuvering. This talk aims to present examples of responsible practices for spacecraft Owners/Operators (O/O) to consider for lowering collision risks and operating safely in space (from LEO and beyond) in a stable and sustainable manner. As technology and innovation continues to improve upon existing capabilities, what kind of new challenges are presented in the SSA community? Can space exploration and commercial ventures thrive while keeping paramount the safety and protection of the space environment? What are the challenges and opportunities that need to be addressed and considered for space situational awareness in Cis-Lunar Space? It may prove useful for entities offering, or intending to offer, SSA or Conjunction Assessment (CA) services to consider such examples of responsible practices to protect the space environment for future use by all.

Collision Avoidance↗
DOE OSTI2026

Sample Preparation Laboratory (SPL) Best Practices: CGD as the Primary Acceptance Method

The traditional paradigm applied to the construction of nuclear safety related systems, structures, and components (SSCs), like SPL, involves an owner/licensee hiring an EPC firm with an NQA 1 program to manage the engineering, procurement, and construction of the desired SSC. This traditional approach would have posed significant barriers to the successful completion of the SPL. As a smaller capital project, in the $\$$100–$\$$200 million range, there was concern that employing one of the larger EPC companies would escalate costs and extend the projected schedule beyond what would be feasible for the Department of Energy (DOE). The traditional acceptance method employed for nuclear facilities with credited safety functions requires the use of an EPC firm applying American Society of Mechanical Engineers (ASME) NQA 1 nuclear quality assurance (NQA) to accept safety SSCs. In lieu of this approach, INL elected to apply its own NQA 1 program to hire an EPC firm operating a commercial quality program. This method used commercial grade dedication (CGD) as outlined in NQA 1 which had not been applied at this scale. Use of the commercial supply chain was identified as a key factor to the successful completion of SPL. Favorable conditions enabling the use of CGD included: • INL serving as both the designer and the design authority • Design created by an NQA 1 qualified source • A mature CGD program • Availability of a CGD subject matter expert (SME) • A strong construction management program. This white paper elaborates on the methodology employed in the construction of the SPL, the successes achieved, and best practices implemented.

42 - ENGINEERING↗
DOE OSTI2026

Multi‐Model Ensembles in Ecosystem Modeling: Challenges and Best Practices for Decision‐Making

Ecosystem models are increasingly central to the decision-making for environmental policy, conservation planning, and climate-related investments. Yet, the growing reliance on Multi-Model Ensembles (MMEs) of ecosystem models by practitioners and policymakers, sometimes under tight timelines and imperfect information, has frequently outpaced the scientific rigor required to ensure ensemble reliability. Here, MMEs refer to approaches that combine targeted predictions from multiple models with the expectation of improving robustness and quantifying predictive uncertainty. Poorly designed MMEs may create a false sense of confidence and lead to suboptimal policy and market decisions. This perspective argues that robust decision-making-relevant MMEs must be grounded on two pillars: (1) rigorous Model Intercomparison Projects (MIPs), which identify inter-model agreement and disagreement, characterize model uncertainties, and evaluate robustness with observationally based benchmarks—MIPs' diagnostic evaluation is so critical that it must be needed to drive MME's decision in model selection and weighting, especially when only a limited number of models available; and (2) co-design by both stakeholders and scientists to ensure that scenarios, metrics and uncertainty requirements provide decision-relevant information. Building upon the past success and lessons from the existing MIPs-MMEs efforts (e.g., climate/Earth system/crop), we derived the theoretical basis for MMEs, addressed their specific challenges in ecosystem modeling, and highlighted proper consideration of model numbers and diversity, risk of model inter-dependence, effective calibration of model parameters, possible overdue of some ecosystem model development, critical roles of open benchmark data across a wide range of conditions, and suggested use of Artificial Intelligence to support MIPs-MMEs. We highlighted the under-recognized opportunity for MIPs and MMEs to drive scientific progress and innovation through identifying better performing models, systematic benchmarking, feedback loops, and targeted model improvement. By following actionable best practice guidelines, MMEs can evolve from ad hoc aggregation of models into a trusted backbone of environmental policy and decision-making.

ecosystem modeling↗
NASA NTRS2016

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗
NASA NTRS2014

NASA Orbital Debris Requirements and Best Practices

Limitation of orbital debris accumulation is an international and national concern, reflectedin NASA debris limitation requirements. These requirements will be reviewed, along with some practices that can be employed to achieve the requirements.

Best Practices↗