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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 721 records · Page 40

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NASA NTRS2002

Deep Space Design Environments for Human Exploration

Mission scenarios outside the Earth's protective magnetic shield are being studied. Included are high usage assets in the near-Earth environment for casual trips, for research, and for commercial/operational platforms, in which career exposures will be multi-mission determined over the astronaut's lifetime. The operational platforms will serve as launching points for deep space exploration missions, characterized by a single long-duration mission during the astronaut's career. The exploration beyond these operational platforms will include missions to planets, asteroids, and planetary satellites. The interplanetary environment is evaluated using convective diffusion theory. Local environments for each celestial body are modeled by using results from the most recent targeted spacecraft, and integrated into the design environments. Design scenarios are then evaluated for these missions. The underlying assumptions in arriving at the model environments and their impact on mission exposures within various shield materials will be discussed.

Wilson, J. W.↗

NASA NTRS1998

On-board Science Understanding: NASA Ames' Efforts

In the near future NASA intends to explore various regions of our solar system using robotic devices such as rovers, spacecraft, airplanes, and/or balloons. Such platforms will likely carry imaging devices, and a variety of analytical instruments intended to evaluate the chemical and mineralogical nature of the environment(s) that they encounter. Historically, mission operations have involved: (1) return of scientific data from the craft; (2) evaluation of the data by space scientists; (3) recommendations of the scientists regarding future mission activity; (4) commands for achieving these activities being transmitted to the craft; and (5) the activity being undertaken. This cycle is then repeated for the duration of the mission with command opportunities once or perhaps twice per day. In a rapidly changing environment, such as might be encountered by a rover traversing hundreds of meters a day or a spacecraft encountering an asteroid, this historical cycle is not amenable to rapid long range traverses, discovery of novelty, or rapid response to any unexpected situations. In addition to real-time response issues, the nature of imaging and/or spectroscopic devices are such that tremendous data volumes can be acquired, for example during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios clearly require the enabling of some crucial decisions to be made on-board by these robotic explorers. These decisions transcend the electromechanical control, health, and navigation issues associated with robotic operations. Instead they focus upon a long term goal of automating scientific discovery based upon data returned by sensors of the robot craft. Such an approach would eventually enable it to understand what is interesting because the data deviates from expectations generated by current theories/models of planetary processes that could have resulted in the observed data. Such interesting data and/or conclusions can then be selectively transmitted to Earth thus reducing memory and communications demands.

Roush, Ted L.↗

NASA NTRS2004

Deep space environments for human exploration

NASA Center LaRC↗

NASA NTRS2016

Development of a Mars Environmental Control and Life Support System (ECLSS).

ECLS systems for very long-duration human missions to Mars will be designed to operate reliably for many years and will never be returned to Earth. The need for high reliability is driven by unsympathetic abort scenarios. Abort from a Mars mission could be as long as 450 days to return to Earth. Simply put, the goal of an ECLSS is to duplicate the functions the Earth provides in terms of human living and working on our home planet but without the benefit of the Earth's large buffers - the atmospheres, the oceans and land masses. With small buffers a space-based ECLSS must operate as a true dynamic system rather than independent processors taking things from tanks, processing them, and then returning them to product tanks. Key is a development process that allows for a logical sequence of validating successful development (maturation) in a stepwise manner with key performance parameters (KPPs) at each step; especially KPPs for technologies evaluated in a full systems context with human crews on Earth and on space platforms such as the ISS. This paper will explore the implications of such an approach to ECLSS development and the roles of ground and space-based testing necessary to develop a highly reliable life support system for long duration human exploration missions. Historical development and testing of ECLS systems from Mercury to the International Space Station (ISS) will be reviewed. Current work as well as recommendations for future work will be described.

Henninger, Donald L.↗

NASA NTRS2016

Integrated Human-in-the-Loop Ground Testing - Value, History, and the Future

Systems for very long-duration human missions to Mars will be designed to operate reliably for many years and many of these systems will never be returned to Earth. The need for high reliability is driven by the requirement for safe functioning of remote, long-duration crewed systems and also by unsympathetic abort scenarios. Abort from a Mars mission could be as long as 450 days to return to Earth. The key to developing a human-in-the-loop architecture is a development process that allows for a logical sequence of validating successful development in a stepwise manner, with assessment of key performance parameters (KPPs) at each step; especially important are KPPs for technologies evaluated in a full systems context with human crews on Earth and on space platforms such as the ISS. This presentation will explore the implications of such an approach to technology development and validation including the roles of ground and space-based testing necessary to develop a highly reliable system for long duration human exploration missions. Historical development and systems testing from Mercury to the International Space Station (ISS) to ground testing will be reviewed. Current work as well as recommendations for future work will be described.

Henninger, Donald L.↗

NASA NTRSDate not supplied

Structural Architectures for Self-Erecting Lunar Towers

The load carrying performance for deployable lunar tower architectures utilizing thin-ply composite booms are parametrically evaluated in this paper. These self-erecting towers support a communications and sensor platform on the lunar surface. The primary design consists of the Corrugated Rollable Tubular Boom (COROTUB) acting as the primary mast of the tower which supports the payload tip mass. Guy wires connecting the boom tip to spreader bars attached at the base deployer serve to correct any lateral eccentricities and provide dimensional stability. The analysis compares the maximum tip mass that this primary design can carry relative to a reference design that does not contain any guy wires or spreader bars. The results provide insights into whether the additional system mass and complexity associated with the cable-stayed design is worth the increased payload mass that can be supported. By setting the design limiting condition to a nominal maximum allowable deflection, the analysis reveals that primary design outperforms reference design for the majority of the design space. This outcome is found to be the case when the spreader bar length relative to the tower height exceeds7 a critical value. The analysis is extended to lunar towers with Collapsible Tubular Mast (CTM) booms, and similar trends are observed.

Jacob G Daye↗

NASA NTRSDate not supplied

Structural Architectures for Self-Erecting Lunar Towers

The load carrying performance for deployable lunar tower architectures utilizing thin-ply composite booms are parametrically evaluated in this paper. These self-erecting towers support a communications and sensor platform on the lunar surface. The primary design consists of the Corrugated Rollable Tubular Boom (COROTUB) acting as the primary mast of the tower which supports the payload tip mass. Guy wires connecting the boom tip to spreader bars attached at the base deployer serve to correct any lateral eccentricities and provide dimensional stability. The analysis compares the maximum tip mass that this primary design can carry relative to a reference design that does not contain any guy wires or spreader bars. The results provide insights into whether the additional system mass and complexity associated with the cable-stayed design is worth the increased payload mass that can be supported. By setting the design limiting condition to a nominal maximum allowable deflection, the analysis reveals that primary design outperforms reference design for the majority of the design space. This outcome is found to be the case when the spreader bar length relative to the tower height exceeds a critical value. The analysis is extended to lunar towers with Collapsible Tubular Mast (CTM) booms, and similar trends are observed.

Jacob G Daye↗

NASA NTRS2023

Airborne Lightning Observatory for FEGS and TGFs (ALOFT)

The ALOFT campaign is a unique suborbital campaign to advance the science of highenergy radiation emissions from thunderstorms, validate existing spaceborne lightning mappers and evaluate design concepts for next-generation mappers, and study convection from a suborbital platform. ALOFT is a collaboration between NASA, the University of Bergen, and other institutions that will fly the ER-2 aircraft over tropical thunderstorms around the Gulf of Mexico, Central America, and the Caribbean. The payload will consist of lightning detectors, gamma-ray scintillators, and a mixture of passive and/or active microwave sensors. Supporting the flights will be a diverse groundbased network of lightning instruments spread across the region of interest.

Nikolai Ostgaard↗

DOE OSTI2020

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗

DOE OSTI2021

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what–if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what–if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what–if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what–if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2010

Evaluation of Shortwave Infrared Atmospheric Correction for Ocean Color Remote Sensing of Chesapeake Bay

The NASA Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODIS-Aqua) provides a viable data stream for operational water quality monitoring of Chesapeake Bay. Marine geophysical products from MODIS-Aqua depend on the efficacy of the atmospheric correction process, which can be problematic in coastal environments. The operational atmospheric correction algorithm for MODIS-Aqua requires an assumption of negligible near-infrared water-leaving radiance, nL(sub w)(NIR). This assumption progressively degrades with increasing turbidity and, as such, methods exist to account for non-negligible nL(sub w)(NIR) within the atmospheric correction process or to use alternate radiometric bands where the assumption is satisfied, such as those positioned within shortwave infrared (SWIR) region of the spectrum. We evaluated a decade-long time-series of nL(sub w)(lambda) from MODIS-Aqua in Chesapeake Bay derived using NIR and SWIR bands for atmospheric correction. Low signal-to-noise ratios (SNR) for the SWIR bands of MODIS-Aqua added noise errors to the derived radiances, which produced broad, flat frequency distributions of nL(sub w)(lambda) relative to those produced using the NIR bands. The SWIR approach produced an increased number of negative nL(sub w)(lambda) and decreased sample size relative to the NIR approach. Revised vicarious calibration and regional tuning of the scheme to switch between the NIR and SWIR approaches may improve retrievals in Chesapeake Bay, however, poor SNR values for the MODIS-Aqua SWIR bands remain the primary deficiency of the SWIR-based atmospheric correction approach.

Werdell, P. Jeremy↗

DOE OSTI2026

Livewire: A Model Platform for Data Quality Assessment and AI Readiness Across DOE Missions

High-quality, well-governed data is essential for accelerating discovery and achieving operational excellence across DOE and national laboratory missions. The Livewire Data Platform is a DOE-supported platform that offers automated assessments of data quality, standardization, provenance, and Artificial Intelligence (AI) readiness. It allows researchers and data practitioners to systematically and easily evaluate datasets against established governance criteria and prepare them for advanced analytics. Livewire addresses critical challenges in DOE's data ecosystem with integrated capabilities for metadata validation, provenance tracking, and schema alignment. This platform's automated workflows assist users in identifying data quality gaps, enhancing interoperability between datasets collected from various stakeholders, and ensuring compliance with DOE data standards, all while reducing manual curation efforts. Additionally, we will discuss its AI readiness framework, which is being developed to prepare datasets for training models, developing advanced analytic tools, and machine learning applications. Using some of the more than one hundred tabular datasets on Livewire, processed with this open-source methodology, we will demonstrate how Livewire can serve as a model for scalable, standards-driven data management. This approach provides a pathway to leverage existing and future datasets within the DOE, boosting innovation and efficiency across national laboratories.

33 - ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Topical Report on Water Balance Model Development and Initial Application

This topical report summarizes results from developing a generic dynamic water balance tool which can be used by coal-fired power plant operators to evaluate FGD water management strategies. EPRI is using a statistical software model created on the GoldSim platform and data from coal-fired energy plants to determine the fraction of power plant water needs that can be satisfied by electrodialysis reversal treatment and, correspondingly, the discharge volume and/or byproducts that still need to be managed. The generic model is designed to accept a number of easily obtainable process variables and generate probabilities of resultant water characteristics. The model is also constructed as a universal process flow; one that can be adjusted to accommodate most major components of an FGD blowdown handling system. The generic model is dynamic and utilizes user-inputted operational variation in water quality and quantity to best provide a probabilistic representation of potential performance outcomes. In order to account for complexities of water composition and treatment, a separate chemical modeling software is used to evaluate water chemistry and unit operation performance. The thermodynamic modeling software, OLI Studio, is employed to convert ion data from laboratory analyses into balanced molecular concentrations that are classified as dissolved and suspended solids. The dynamic water model is designed to import a total of 11 species commonly found in FGD blowdown water as molecular concentrations.Water management unit operations are used in the model and categorized by either physical unit operation blocks or chemical unit operations blocks. As the name implies, the physical water treatment blocks are unit operations that are exclusively physical changes to the system (e.g., separations and volume changes). The chemical water treatment blocks are unit operations where chemical changes occur and require the use of OLI Studio to characterize subsequent streams. Water and material balances from three unique coal-fired power plants were obtained and preliminary modeling on the dynamic water balance tool was performed using the extracted data from these power plants. These three power plants were chosen due to their unique configurations and water profiles that represented a variety of operational changes. Results from using the dynamic tool with the three plant configurations are presented and discussed in the context of the existing tool and planned future capabilities.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

The Utility of Satellites and Autonomous Remote Sensing Platforms for Monitoring Offshore Aquaculture Farms: A Case Study for Canopy Forming Kelps

The emerging sector of offshore kelp aquaculture represents an opportunity to produce biofuel feedstock to help meet growing energy demand. Giant kelp represents an attractive aquaculture crop due to its rapid growth and production, however precision farming over large scales is required to make this crop economically viable. These demands necessitate high frequency monitoring to ensure outplant success, maximum production, and optimum quality of harvested biomass, while the long distance from shore and large necessary scales of production makes in person monitoring impractical. Remote sensing offers a practical monitoring solution and nascent imaging technologies could be leveraged to provide daily products of the kelp canopy and subsurface structures over unprecedented spatial scales. Here, we evaluate the efficacy of remote sensing from satellites and aerial and underwater autonomous vehicles as potential monitoring platforms for offshore kelp aquaculture farms. Decadal-scale analyses of the Southern California Bight showed that high offshore summertime cloud cover restricts the ability of satellite sensors to provide high frequency direct monitoring of these farms. By contrast, daily monitoring of offshore farms using sensors mounted to aerial and underwater drones seems promising. Small Unoccupied Aircraft Systems (sUAS) carrying lightweight optical sensors can provide estimates of canopy area, density, and tissue nitrogen content on the time and space scales necessary for observing changes in this highly dynamic species. Underwater color imagery can be rapidly classified using deep learning models to identify kelp outplants on a longline farm and high acoustic returns of kelp pneumatocysts from side scan sonar imagery signal an ability to monitor the subsurface development of kelp fronds. Current sensing technologies can be used to develop additional machine learning and spectral algorithms to monitor outplant health and canopy macromolecular content, however future developments in vehicle and infrastructure technologies are necessary to reduce costs and transcend operational limitations for continuous deployment in an offshore setting.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Quantitative evaluation of common cause failures in high safety-significant safety-related digital instrumentation and control systems in nuclear power plants

Digital instrumentation and control (DI&C) systems at nuclear power plants (NPPs) have many advantages over analog systems. They are proven to be more reliable, cheaper, and easier to maintain given obsolescence of analog components. However, they also pose new engineering and technical challenges, such as possibility of common cause failures (CCFs) unique to digital systems. Here this paper proposes a Platform for Risk Assessment of DI&C (PRADIC) that is developed by Idaho National Laboratory (INL). A methodology for evaluation of software CCFs in high safety-significant safety-related DI&C systems of NPPs was developed as part of the framework. The framework integrates three stages of a typical risk assessment—qualitative hazard analysis and quantitative reliability and consequence analyses. The quantified risks compared with respective acceptance criteria provide valuable insights for system architecture alternatives allowing design optimization in terms of risk reduction and cost savings. A comprehensive case study performed to demonstrate the framework's capabilities is documented here in this paper. Results show that the PRADIC is a powerful tool capable to identify potential digital-based CCFs, estimate their probabilities, and evaluate their impacts on system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Grid impact analysis using controller-hardware-in-the-loop for high-power vehicle charging stations

A controller-hardware-in-the-loop (CHIL) architecture for the evaluation of grid impacts arising from high-power vehicle charging stations is presented in this paper. Unlike simulation-based studies, the proposed method can be used to capture the interactions of the grid and the charging load along with charger controllers in real time. The proposed method can be used to evaluate the impact of charging load on the grid in terms of voltage variations and line congestion. The proposed CHIL platform allows for de-risking the vehicle charging station deployment by simulating the complex interactions among all the components of a vehicle charging station - i.e., the grid, vehicle, and charger controller - in a realistic manner before using the charging station in a grid. Further, the proposed CHIL approach can be used to evaluate the voltage regulation causalities of the vehicle charging station. Experimental results are presented in the paper to illustrate the applicability of the proposed method in a laboratory environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗

DOE OSTI2021

Characterization of suspended membrane waveguides towards a photonic atom trap integrated platform

We demonstrate an optical waveguide device, capable of supporting the high, in-vacuum, optical power necessary for trapping a single atom or a cold atom ensemble with evanescent fields. Our photonic integrated platform, with suspended membrane waveguides, successfully manages optical powers of 6 mW (500 μ m span) to nearly 30 mW (125 μ m span) over an un-tethered waveguide span. This platform is compatible with laser cooling and magneto-optical traps (MOTs) in the vicinity of the suspended waveguide, called the membrane MOT and the needle MOT, a key ingredient for efficient trap loading. We evaluate two novel designs that explore critical thermal management features that enable this large power handling. This work represents a significant step toward an integrated platform for coupling neutral atom quantum systems to photonic and electronic integrated circuits on silicon.

36 MATERIALS SCIENCE↗