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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Reducing Airborne Infectious Aerosol Exposure

Since beginning its work in late March 2020, the ASHRAE Epidemic Task Force (ETF) has produced a large set of guidance documents totaling hundreds of pages, all of which can be found at the ASHRAE COVID-19 resources web pages (www.ashrae.org/COVID19). This guidance has evolved as scientific understanding has increased and circumstances have changed, necessitating several updates. The initial, one-page “Core Recommendations” document, approved in January 2021, was written to provide a concise summary of the most current task force recommendations for the benefit of the public and to promote consistency between guidance documents developed by different ETF teams. This column includes the Core Recommendations (in bold) with added commentary to provide the rationale for each.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2024

Combining Large Datasets - Cancer Moonshot Task Group Final Summary

In February 2022, President Biden re-ignited the Cancer Moonshot with bold new goals: to reduce the cancer death rate by half within 25 years and improve the lives of people with cancer and cancer survivors. To achieve these ambitious goals, the White House convened the first-ever Cancer Cabinet, bringing together departments and agencies from across the federal government to end cancer as we know it.The Cancer Cabinet convened three task forces and supporting task groups, including the Data and Innovation Task Force, which supported the Cancer Moonshot priority to “Deliver innovation to patients and communities.” In early 2023, the “Combining Large Datasets” (CoLD) Task Group was created within the Data and Innovation Task Force. The scope of the CoLD Task Group was how federal agencies combine large datasets for broad applications across cancer prevention and control, including nutrition, epidemiology, and military/Veteran health. Within this scope, the group sought to better leverage the immense potential of data and power of data tools to increase our understanding of cancer incidence, causes, mortality, treatments, prevention, outcomes, costs, and all other aspects of the burden of cancer.

data integration↗
DOE OSTI2018

Factors determining the exposure of dairy farmers to thoracic organic dust

Highlights: • Dairy farming exposes to thoracic dusts containing bacteria and moulds. • Specific tasks and farm characteristics control exposures to thoracic organic dusts. • Temperature and hygrometry also control the levels of organic dust exposure. Bronchial respiratory diseases are more common in dairy farmers than in the general population, perhaps because the repeated inhalation of organic dust contributes to the development of these disorders. However, the factors determining the exposure of farmers to particles that can enter the lower bronchial tract and interact with it, i.e. the thoracic fraction of the inhalable dust, remain to be identified. We therefore measured the exposure of dairy farmers to thoracic organic dust and identified the farm features and tasks that increased exposure. We measured thoracic particles (n = 110) and farm characteristics and occupational tasks in 29 Brittany dairy farms. The mean (GM) (geometric standard deviation, GSD) concentration of thoracic dust in air inhaled by farmers was 0.24 mg/m{sup 3} (2.8) and the concentrations of endotoxins, Gram-positive bacteria and fungi in the thoracic fraction were 128 EU/m{sup 3} (4.0), 960 CFU/m{sup 3} (6.3) and 690 CFU/m{sup 3} (5.4), respectively. Model-based estimates of the association between exposure, farm features and tasks indicated that manual grain and feed handling and mechanical bedding spreading significantly increased exposure to thoracic dust, endotoxins, bacteria and fungi. Exposure to bacteria and fungi was reduced by cowsheds divided into cubicles, whereas using automatic muck scrappers in alleyway and automatic milking tended to increase exposure to bacteria and endotoxins. Finally, exposure to endotoxin and fungi were reduced by warmer farm buildings and well-ventilated buildings having walls with large openings. In conclusions, major occupational tasks and specific farm features determine the exposure of Breton dairy farmers to thoracic organic dust.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Towards Diverse and Representative Global Pretraining Datasets for Remote Sensing Foundation Models

The design of a pretraining dataset is emerging as a critical component for the generality of foundation models. In the remote sensing realm, large volumes of imagery and benchmark datasets exist that can be leveraged to pretrain foundation models, however using this imagery in absence of a well-crafted sampling strategy is inefficient and has the potential to create biased and less generalizable models. Here, we provide a discussion and vision for the curation and assessment of pretraining datasets for remote sensing geospatial foundation models. We highlight the importance of geographic, temporal, and image acquisition diversity and review possible strategies to enable such diversity at global scale. In addition to these characteristics, support for various spatial-temporal pretext tasks within the dataset is also critical. Ultimately, our primary objective is to place emphasis on and draw attention to the data curation stage of the foundation model development pipeline. By doing so, we think it is possible to reduce biases of geospatial foundation models, as well as enable broader generalization to downstream remote sensing tasks and applications.

Arndt, Jacob↗
NASA NTRS1996

Soot and Radiation Measurements in Microgravity Jet Diffusion Flames

The subject of soot formation and radiation heat transfer in microgravity jet diffusion flames is important not only for the understanding of fundamental transport processes involved but also for providing findings relevant to spacecraft fire safety and soot emissions and radiant heat loads of combustors used in air-breathing propulsion systems. Our objectives are to measure and model soot volume fraction, temperature, and radiative heat fluxes in microgravity jet diffusion flames. For this four-year project, we have successfully completed three tasks, which have resulted in new research methodologies and original results. First is the implementation of a thermophoretic soot sampling technique for measuring particle size and aggregate morphology in drop-tower and other reduced gravity experiments. In those laminar flames studied, we found that microgravity soot aggregates typically consist of more primary particles and primary particles are larger in size than those under normal gravity. Comparisons based on data obtained from limited samples show that the soot aggregate's fractal dimension varies within +/- 20% of its typical value of 1.75, with no clear trends between normal and reduced gravity conditions. Second is the development and implementation of a new imaging absorption technique. By properly expanding and spatially-filtering the laser beam to image the flame absorption on a CCD camera and applying numerical smoothing procedures, this technique is capable of measuring instantaneous full-field soot volume fractions. Results from this technique have shown the significant differences in local soot volume fraction, smoking point, and flame shape between normal and reduced gravity flames. We observed that some laminar flames become open-tipped and smoking under microgravity. The third task we completed is the development of a computer program which integrates and couples flame structure, soot formation, and flame radiation analyses together. We found good agreements between model predictions and experimental data for laminar and turbulent flames under both normal and reduced gravity. We have also tested in the laboratory the techniques of rapid-insertion fine-wire thermocouples and emission pyrometry for temperature measurements. These techniques as well as laser Doppler velocimetry and spectral radiative intensity measurement have been proposed to provide valuable data and improve the modeling analyses.

Ku, Jerry C.↗
NASA NTRS2013

MPST Software: grl_pef_check

This innovation is a tool used to verify and validate spacecraft sequences at the predicted events file (PEF) level for the GRAIL (Gravity Recovery and Interior Laboratory, see http://www.nasa. gov/mission_pages/grail/main/index. html) mission as part of the Multi-Mission Planning and Sequencing Team (MPST) operations process to reduce the possibility for errors. This tool is used to catch any sequence related errors or issues immediately after the seqgen modeling to streamline downstream processes. This script verifies and validates the seqgen modeling for the GRAIL MPST process. A PEF is provided as input, and dozens of checks are performed on it to verify and validate the command products including command content, command ordering, flight-rule violations, modeling boundary consistency, resource limits, and ground commanding consistency. By performing as many checks as early in the process as possible, grl_pef_check streamlines the MPST task of generating GRAIL command and modeled products on an aggressive schedule. By enumerating each check being performed, and clearly stating the criteria and assumptions made at each step, grl_pef_check can be used as a manual checklist as well as an automated tool. This helper script was written with a focus on enabling the user with the information they need in order to evaluate a sequence quickly and efficiently, while still keeping them informed and active in the overall sequencing process. grl_pef_check verifies and validates the modeling and sequence content prior to investing any more effort into the build. There are dozens of various items in the modeling run that need to be checked, which is a time-consuming and errorprone task. Currently, no software exists that provides this functionality. Compared to a manual process, this script reduces human error and saves considerable man-hours by automating and streamlining the mission planning and sequencing task for the GRAIL mission.

Call, Jared A.↗
NASA NTRS2019

Generation of a Reduced-Order Model of an Unmanned Combat Air Vehicle Using Indicial Response Functions

Within the NATO STO AVT-251 Task Group, a generic Unmanned Combat Air Vehicle (UCAV) planform was redesigned based on requirements derived from parts of the flight envelope of the defined mission. Because of the lambda-shape planform and associated flow phenomena including shocks and vortices, the aerodynamic design process relies heavily on high-fidelity predictions from computational fluid dynamics (CFD). These simulations enable accurate flight dynamics predictions, allowing for the identification of any potential performance issues early in the design process. Potentially, a complete flight dynamics model can be derived from CFD calculations provided that the underlying reduced order model (ROM) captures the underlying physics contained within the CFD results. This work investigates the creation of a nonlinear ROM using indicial response functions. The response functions are obtained using a grid motion approach that separates the effects of angle of attack and pitch rate. This approach is demonstrated using three different CFD codes from various organizations: ENSOLV at Royal Netherlands Aerospace Centre, USM3D at NASA Langley Research Center, and Kestrel at the United States Air Force Academy. ROM predictions were generated for a manoeuver resembling a low-speed pull-up. The predictions are found to be sensitive to the quality of the steady-state solutions from which step-response calculations were started, as well as the convergence of the step responses themselves. Nevertheless, the indicial response method is shown to provide aerodynamic predictions with acceptable accuracy including transient effects, and as such is a promising method for computationally efficient flight dynamics predictions.

Michel P.C. van Rooij↗
NASA NTRS1998

Human Mars Missions: Cost Driven Architecture Assessments

This report investigates various methods of reducing the cost in space transportation systems for human Mars missions. The reference mission for this task is a mission currently under study at NASA. called the Mars Design Reference Mission, characterized by In-Situ propellant production at Mars. This study mainly consists of comparative evaluations to the reference mission with a view to selecting strategies that would reduce the cost of the Mars program as a whole. One of the objectives is to understand the implications of certain Mars architectures, mission modes, vehicle configurations, and potentials for vehicle reusability. The evaluations start with year 2011-2014 conjunction missions which were characterized by their abort-to-the-surface mission abort philosophy. Variations within this mission architecture, as well as outside the set to other architectures (not predicated on an abort to surface philosophy) were evaluated. Specific emphasis has been placed on identifying and assessing overall mission risk. Impacts that Mars mission vehicles might place upon the Space Station, if it were to be used as an assembly or operations base, were also discussed. Because of the short duration of this study only on a few propulsion elements were addressed (nuclear thermal, cryogenic oxygen-hydrogen, cryogenic oxygen-methane, and aerocapture). Primary ground rules and assumptions were taken from NASA material used in Marshall Space Flight Center's own assessment done in 1997.

Interplanetary Mission↗
NASA NTRS1995

Geometric modeling for computer aided design

The primary goal of this grant has been the design and implementation of software to be used in the conceptual design of aerospace vehicles particularly focused on the elements of geometric design, graphical user interfaces, and the interaction of the multitude of software typically used in this engineering environment. This has resulted in the development of several analysis packages and design studies. These include two major software systems currently used in the conceptual level design of aerospace vehicles. These tools are SMART, the Solid Modeling Aerospace Research Tool, and EASIE, the Environment for Software Integration and Execution. Additional software tools were designed and implemented to address the needs of the engineer working in the conceptual design environment. SMART provides conceptual designers with a rapid prototyping capability and several engineering analysis capabilities. In addition, SMART has a carefully engineered user interface that makes it easy to learn and use. Finally, a number of specialty characteristics have been built into SMART which allow it to be used efficiently as a front end geometry processor for other analysis packages. EASIE provides a set of interactive utilities that simplify the task of building and executing computer aided design systems consisting of diverse, stand-alone, analysis codes. Resulting in a streamlining of the exchange of data between programs reducing errors and improving the efficiency. EASIE provides both a methodology and a collection of software tools to ease the task of coordinating engineering design and analysis codes.

Schwing, James L.↗
NASA NTRS2013

Proof-of-Concept of a Networked Validation Environment for Distributed Air/Ground NextGen Concepts

The National Airspace System (NAS) must be improved to increase capacity, reduce flight delays, and minimize environmental impacts of air travel. NASA has been tasked with aiding the Federal Aviation Administration (FAA) in NAS modernization. Automatic Dependent Surveillance-Broadcast (ADS-B) is an enabling technology that is fundamental to realization of the Next Generation Air Transportation System (NextGen). Despite the 2020 FAA mandate requiring ADS-B Out equipage, airspace users are lacking incentives to equip with the requisite ADS-B avionics. A need exists to validate in flight tests advanced concepts of operation (ConOps) that rely on ADS-B and other data links without requiring costly equipage. A potential solution is presented in this paper. It is possible to emulate future data link capabilities using the existing in-flight Internet and reduced-cost test equipment. To establish proof-of-concept, a high-fidelity traffic operations simulation was modified to include a module that simulated Internet transmission of ADS-B messages. An advanced NASA ConOp, Flight Deck Interval Management (FIM), was used to evaluate technical feasibility. A preliminary assessment of the effects of latency and dropout rate on FIM was performed. Flight hardware that would be used by proposed test environment was connected to the simulation so that data transfer from aircraft systems to test equipment could be verified. The results indicate that the FIM ConOp, and therefore, many other advanced ConOps with equal or lesser response characteristics and data requirements, can be evaluated in flight using the proposed concept.

Grisham, James↗
DOE OSTI2024

BAD2matrix: Phylogenomic matrix concatenation, indel coding, and more

Common steps in phylogenomic matrix production include biological sequence concatenation, morphological data concatenation, insertion/deletion (indel) coding, gene content (presence/absence) coding, removing uninformative characters for parsimony analysis, recording with reduced amino acid alphabets, and occupancy filtering. Existing software does not accomplish these tasks on a phylogenomic scale using a single program. BAD2matrix is a Python script that performs the above-mentioned steps in phylogenomic matrix construction for DNA or amino acid sequences as well as morphological data. The script works in UNIX-like environments (e.g., LINUX, MacOS, Windows Subsystem for LINUX).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Field demonstration and implementation analysis of model predictive control in an office HVAC system

Model Predictive Control (MPC) is a promising technique to address growing needs for heating, ventilation, and air-conditioning (HVAC) systems to operate more efficiently and with greater flexibility. However, due to a number of factors, including the required implementation expertise, lack of high quality data, and a risk-adverse industry, MPC has yet to gain widespread adoption. While many previous studies have shown the advantages of MPC, few analyzed the implementation effort and associated practical challenges. In addition, previous work has developed an open-source, Modelica-based tool-chain that automatically generates optimal control, parameter estimation, and state estimation problems aimed at facilitating MPC implementation. Therefore, this study demonstrates usage of this tool-chain to implement MPC in a real office building, discusses practical challenges of implementing MPC, and estimates the implementation effort associated with various tasks in order to inform the development of future workflows and serve as an initial benchmark for their impact on reducing implementation effort. This study finds that the implemented MPC saves approximately 40% of HVAC energy over the existing control during a two-month trial period and that tasks related to data collection and controller deployment activities can each require as much effort as model generation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Advanced Laboratory and Field Arrays: Technical Report for Autonomous Monitoring & Intervention (Task 2)

The goal for this task was to develop software for an autonomous underwater vehicle (AUV) capable of performing inspection, monitoring, and intervention operations in marine renewable energy arrays, employing motion planning and probabilistic navigation methods. Inspection and manipulation tasks were chosen to be applicable to multiple device types without requiring expensive components. Minimal human intervention reduces costs and also improves efficiency. Using AUVs for inspection and monitoring with limited human intervention and low-cost infrastructure is viewed as critical to the strategy for bringing down O&M costs. The final deliverable for this task was to enable a decrease in the time for maintenance and intervention in marine renewable energy arrays by up to 30% versus using tele-operated ROVs.

13 HYDRO ENERGY↗
NASA NTRS1992

On the acquisition and representation of procedural knowledge

Historically knowledge acquisition has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some of some types of knowledge, little attention has been devoted to procedural knowledge. NASA personnel frequently perform tasks that are primarily procedural in nature. Previous work is reviewed in the field of knowledge acquisition and then focus on knowledge acquisition for procedural tasks with special attention devoted to the Navy's VISTA tool. The design and development is described of a system for the acquisition and representation of procedural knowledge-TARGET (Task Analysis and Rule Generation Tool). TARGET is intended as a tool that permits experts to visually describe procedural tasks and as a common medium for knowledge refinement by the expert and knowledge engineer. The system is designed to represent the acquired knowledge in the form of production rules. Systems such as TARGET have the potential to profoundly reduce the time, difficulties, and costs of developing knowledge-based systems for the performance of procedural tasks.

Saito, T.↗
DOE OSTI2024

ML based control systems for nuclear physics experiments

The Experimental Physics Software and Computing Infrastructure (EPSCI) group at Jefferson Lab is leading the use of machine learning (ML) to enhance control systems in nuclear physics experiments. Collaborating closely with domain experts and data scientists, we have developed an ML-based control system that uses a Gaussian process to dynamically adjust the high voltage of the GlueX Central Drift Chamber. This results in stable detector performance by adapting to environmental changes, thereby reducing the offline calibration effort. Furthermore, we are developing ML-driven systems for optimizing the polarization of photon beams and polarized cryotargets. These systems will maintain the optimal microwave frequency in cryogenic targets and make real-time adjustments to diamond radiators for polarized photon sources, tasks traditionally handled by human operators. By automating these functions, we aim to optimize the polarization, reduce downtime, and minimize human error. This talk will highlight the development of reliable ML-based control systems and the policies to ensure they are both effective and trustworthy.

Jeske, Torri↗
DOE OSTI2017

Comparison of Mutual Awareness in Analog vs. Digital Control Rooms

Control rooms in nuclear power plants are complex, collaborative working environments rife with potential for human error. As control rooms evolve from analog to digital interface environments, crew communication strategies must change as well. Operators in the analog control room operate the plant and communicate with each other with the help of control boards with large control panels, meters, and switches. Reactor operators could choose a particular set of controls on the particular control board which corresponds to the part of the system of interest. Visual display units (VDU), which became a fixture in the control rooms with the shift to digital human-machine interfaces (HMI), bring benefits for safety and flexibility combining information from various sources. With the increase in automation and the use of digital HMIs operators received their personal sitting workstations where they are able to navigate and operate the plant. The amount of information increased as well as the complexity of monitoring and analyzing the system states. Also computerized systems cause operators to get absorbed by their personal screens and reduce interaction between the crew members. Therefore, the collaboration and coordination of task demands requires vigilance and mutual awareness. The level of automation has an influence on the level of mutual awareness experienced by operators in the control rooms. Teams function to carry out highly interdependent tasks, requiring synthesis and sharing of information to achieve common goals. Improving the performance of the team necessitates the operators to focus on the system, the surrounding environment, and situational awareness about the system states. Collaboration of team members is critical when employing the digital operating systems as the acute awareness of the overall progress of the group and individual activities of the operators drives the team to the desired end-states of the plant operations. Out-of-the loop (OOTL) performance problems can be referred to as the lack of supervisory control, system monitoring, and information processing in the digital HMIs. Under some circumstances Senior Reactor Operators (SRO) struggle to follow the actions of other Reactor Operators (RO) because with the new digital interfaces SROs lose track of how the procedures are carried out by ROs, which results in the loss of three way communication. Mutual awareness plays a significant role in keeping the SROs in the loop of plant operations. This paper will investigate, through literature review and expert interviews, the impact and human errors attributed to the increasing complexity of new digital main control rooms. Comparison of the new digital interfaces with the analog interfaces in nuclear power plants has the potential to shed light on increasing mutual awareness and three way communications between the SROs and ROs. Further, identification of the human errors and human actions can provide beneficial information, suggesting significant and critical improvements that can be implemented in the main control rooms to increase safety and reliability of new technology. Additionally, insights on mutual awareness for analog vs. digital control rooms can serve to improve human reliability.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

A digital twin approach to system-level fault detection and diagnosis for improved equipment health monitoring

Automating the task of fault detection and diagnosis is crucial in the effort to reduce the operation and maintenance cost in the nuclear industry. This paper describes a physics-based approach for system-level diagnosis in thermal-hydraulic systems in nuclear power plants. The inclusion of physics information allows for the creation of virtual sensors, which provide improved fault diagnosis capability. The physics information also serves to better constrain diagnostic solutions to the physical domain. As a demonstration, various test cases for fault diagnosis in a high-pressure feedwater system were considered. The use of virtual sensors allows constructing performance models for two first-point feedwater heaters which would not have been possible otherwise due to the limited sensor set. Real-time plant data provided by a utility partner were used to assess the diagnostic approach. The detection of an abnormal event immediate after a plant startup pointed to faulty behaviors in the two first-point feedwater heaters. Further, this double-blind fault diagnosis was subsequently confirmed by the plant operator. In addition, several simulated sensor fault events demonstrated the capability of our algorithms in detecting and discriminating sensor faults.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Task-oriented machine learning surrogates for tipping points of agent-based models

We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for the construction of different types of effective reduced order models from detailed agent-based simulators and the systematic multiscale numerical analysis of their emergent dynamics. The specific tasks of interest here include the detection of tipping points, and the uncertainty quantification of rare events near them. Our illustrative examples are an event-driven, stochastic financial market model describing the mimetic behavior of traders, and a compartmental stochastic epidemic model on an Erdös-Rényi network. We contrast the pros and cons of the different types of surrogate models and the effort involved in learning them. Importantly, the proposed framework reveals that, around the tipping points, the emergent dynamics of both benchmark examples can be effectively described by a one-dimensional stochastic differential equation, thus revealing the intrinsic dimensionality of the normal form of the specific type of the tipping point. This allows a significant reduction in the computational cost of the tasks of interest.

97 MATHEMATICS AND COMPUTING↗