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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Distributed Renewables for Arctic Energy: A Case Study

Alaska is a vast state that stretches into the Arctic Circle. Roughly 140,000 people in the state are dependent on isolated electric grids, traditionally burning expensive fossil fuels. This has negative impacts on air quality and climate. As the climate warms, fuel supply chains and traditional ways of life are threatened. Renewable electric sources offer a clean, resilient alternative with less volatile costs, but there are a variety of technical, social, economic, and political challenges to developing renewable energy systems in remote Arctic communities. Examples include harsh operating conditions, lack of local technical and managerial capacity, complex funding mechanisms, and glacial permitting processes. In this study, we interview one group of communities that are interested in adding renewable energy to their systems to understand the needs and challenges they face, and then another group that has successfully installed renewable energy, to understand how they overcame such challenges and the lessons they learned. Notable results include the importance of local buy-in, education, and technical involvement, procuring external funding sources, inter-community collaboration, installing bespoke systems, and working with reliable equipment suppliers. The goal of this report is to orient and inspire Arctic communities that want to begin their renewable transition, by providing helpful examples and points of contact.

17 WIND ENERGY↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers

With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to optimize manufacturing workflow and processes for improved energy efficiency, equipment reliability, quality, safety, and productivity. This challenges capital cost and complexity for many small and medium-sized manufacturers (SMMs) who heavily rely on people to supervise manufacturing processes and facilities. This research aims to create an affordable, scalable, accessible, and portable (ASAP) solution to automate the supervision of manufacturing processes. The proposed approach seeks to reduce the cost and complexity of smart manufacturing deployment for SMMs through the deployment of consumer-grade electronics and a novel AI development methodology. The proposed system, AI-assisted Machine Supervision (AIMS), provides SMMs with two major subsystems: direct machine monitoring (DMM) and human-machine interaction monitoring (HIM). The AIMS system was evaluated and validated with a case study in 3D printing through the affordable AI accelerator solution of the vision processing unit (VPU).

3D printing↗
NASA NTRS1972

Past and future space flight experiments on man and their spin-off contribution to world health.

The manned space-flight program has created some requirements which were new to the practice of medicine. The remoteness of the patient made it necessary to provide sensing and transmitting capability for various physiologic functions. The space and weight penalties in a spacecraft required that such sensors and related equipment be miniaturized and of a noninterfering nature as far as the crewmen were concerned. The need for continually increasing flight durations created a requirement for a type of equipment reliability previously unknown to medicine. The requirement to protect the crewmen against the environment of space and provide a habitable spacecraft has produced a series of ground-based medical applications.

Berry, C. A.↗
NASA NTRS1990

Robotic lunar surface operations: Engineering analysis for the design, emplacement, checkout and performance of robotic lunar surface systems

The assembly, emplacement, checkout, operation, and maintenance of equipment on planetary surfaces are all part of expanding human presence out into the solar system. A single point design, a reference scenario, is presented for lunar base operations. An initial base, barely more than an output, which starts from nothing but then quickly grows to sustain people and produce rocket propellant. The study blended three efforts: conceptual design of all required surface systems; assessments of contemporary developments in robotics; and quantitative analyses of machine and human tasks, delivery and work schedules, and equipment reliability. What emerged was a new, integrated understanding of hot to make a lunar base happen. The overall goal of the concept developed was to maximize return, while minimizing cost and risk. The base concept uses solar power. Its primary industry is the production of liquid oxygen for propellant, which it extracts from native lunar regolith. Production supports four lander flights per year, and shuts down during the lunar nighttime while maintenance is performed.

Woodcock, Gordon R.↗
NASA NTRS2010

Lunar Landing Operational Risk Model

Characterizing the risk of spacecraft goes beyond simply modeling equipment reliability. Some portions of the mission require complex interactions between system elements that can lead to failure without an actual hardware fault. Landing risk is currently the least characterized aspect of the Altair lunar lander and appears to result from complex temporal interactions between pilot, sensors, surface characteristics and vehicle capabilities rather than hardware failures. The Lunar Landing Operational Risk Model (LLORM) seeks to provide rapid and flexible quantitative insight into the risks driving the landing event and to gauge sensitivities of the vehicle to changes in system configuration and mission operations. The LLORM takes a Monte Carlo based approach to estimate the operational risk of the Lunar Landing Event and calculates estimates of the risk of Loss of Mission (LOM) - Abort Required and is Successful, Loss of Crew (LOC) - Vehicle Crashes or Cannot Reach Orbit, and Success. The LLORM is meant to be used during the conceptual design phase to inform decision makers transparently of the reliability impacts of design decisions, to identify areas of the design which may require additional robustness, and to aid in the development and flow-down of requirements.

Mattenberger, Chris↗
NASA NTRS2013

International R&M/Safety Cooperation Lessons Learned Between NASA and JAXA

Presented are a number of important experiences gained and lessons learned from the collaboration of the National Aeronautics and Space Administration (NASA) and the Japanese Aerospace Exploration Agency (JAXA) on the CoNNeCT (Communications, Navigation, and Networking re-Configurable Testbed) project. Both space agencies worked on the CoNNeCT Project to design, assemble, test, integrate, and launch a communications testbed facility mounted onto the International Space Station (ISS) truss. At the 2012 RAMS, two papers about CoNNeCT were presented: one on Ground Support Equipment Reliability & System Safety, and the other one on combined application of System Safety & Reliability for the flight system. In addition to the logistics challenges present when two organizations are on the opposite side of the world, there is also a language barrier. The language barrier encompasses not only the different alphabet, it encompasses the social interactions; these were addressed by techniques presented in the paper. The differences in interpretation and application of Spaceflight Requirements will be discussed in this paper. Although many, but definitely not all, of JAXA's Spaceflight Requirements were inspired by NASA, there were significant and critically important differences in how they were interpreted and applied. This paper intends to summarize which practices worked and which did not for an international collaborative effort so that future missions may benefit from our experiences. The CoNNeCT flight system has been successfully assembled, integrated, tested, shipped, launched and installed on the ISS without incident. This demonstrates that the steps taken to facilitate international understanding, communication, and coordination were successful and warrant discussion as lessons learned.

Fernandez, Rene↗
NASA NTRSDate not supplied

Update to Developing a Multi-bioreactor Test Stand for the Evaluation of Biofilm Mitigation Technologies

Biofilm formation in spacecraft wastewater systems is a complex and impactful problem. Biomass flowing in these wastewater systems can cause clogging, higher differential pressures, and flow restrictions impacting equipment reliability and function. To explore this issue, the Marshall Space Flight Center’s biofilm test stand was created and has been utilized to examine multiple biofilm mitigation techniques over a long duration test time. This paper is an update to a previous paper, ICES-2021-122, and will serve to discuss the modifications and enhancements to the biofilm test stand. While the previous configuration tested heat treatments and coatings, this phase of testing will examine differing materials, competing bacteria provided by an external bioreactor, a prototype phytoremediation unit, and additional testing with a nutrient filter. Configuration changes include the addition of float switches, adjustment of the drain assembly architecture and additional support hardware for the competing bacteria bioreactor and phytoremediation units.

ECLSS↗
NASA NTRSDate not supplied

Update to Developing a Multi-bioreactor Test Stand for the Evaluation of Biofilm Mitigation Technologies

Biofilm formation in spacecraft wastewater systems is a complex and impactful problem. Biomass flowing in these wastewater systems can cause clogging, higher differential pressures, and flow restrictions impacting equipment reliability and function. To explore this issue, the Marshall Space Flight Center’s biofilm test stand was created and has been utilized to examine multiple biofilm mitigation techniques over a long duration test time. This paper is an update to a previous paper, ICES-2021-122, and will serve to discuss the modifications and enhancements to the biofilm test stand. While the previous configuration tested heat treatments and coatings, this phase of testing will examine differing materials, competing bacteria provided by an external bioreactor, a prototype phytoremediation unit, and additional testing with a nutrient filter. Configuration changes include the addition of float switches, adjustment of the drain assembly architecture and additional support hardware for the competing bacteria bioreactor and phytoremediation units.

ECLSS↗
NASA NTRSDate not supplied

Update to Developing a Multi-bioreactor Test Stand for the Evaluation of Biofilm Mitigation Technologies

Biofilm formation in spacecraft wastewater systems is a complex and impactful problem. Biomass flowing in these wastewater systems can cause clogging, higher differential pressures, and flow restrictions impacting equipment reliability and function. To explore this issue, the Marshall Space Flight Center’s biofilm test stand was created and has been utilized to examine multiple biofilm mitigation techniques over a long duration test time. This paper is an update to a previous paper, ICES-2021-122, and will serve to discuss the modifications and enhancements to the biofilm test stand. While the previous configuration tested heat treatments and coatings, this phase of testing will examine differing materials, competing bacteria provided by an external bioreactor, a prototype phytoremediation unit, and additional testing with a nutrient filter. Configuration changes include the addition of float switches, adjustment of the drain assembly architecture and additional support hardware for the competing bacteria bioreactor and phytoremediation units.

ECLSS↗
DOE OSTI2020

Accelerating Hanford Site Cleanup through Operations Research Modeling - 20238

The Hanford Site cleanup effort will require the integration of dozens of unique facilities and processes, many of which will be first-of-a-kind in implementation and design. Each facility will be governed by its own set of operating logic, configured with a unique array of unit operations, and subject to a set of constraints that will affect its behavior. The collection of facilities have multiple points of interface, making the operations of any one facility potentially significant to the operations of other up- or downstream processes. It is therefore highly desirable to accurately predict these operations, as it allows for Site officials to identify and preempt bottlenecks and vulnerabilities before they unexpectedly inhibit the cleanup mission. With the quantity and complexity of the processes that will be on Site, building a pen-and-paper or even a spreadsheet-assisted model of the cleanup mission quickly becomes overwhelming in scope and inaccurate in execution. The Engineering organization for the Site's Tank Operations Contract (TOC) has therefore implemented the use of operations research (OR) modeling to simulate and predict future operations of Site facilities. These models are created using a discrete event simulation tool that allows for the development of detailed, versatile, and robust models. Not only can these models account for complex logical behaviors, but they can also simulate process details down to the level of vessel sizing, labor utilization, equipment reliability, and resource availability. To date, the TOC has developed OR models for several facilities on Site, including for single-shell tank (SST) farms, double-shell tank (DST) farms, the Effluent Treatment Facility (ETF), and the waste transfer system. These models have focused on identifying bottlenecks and operational constraints, and have been used to quantify the effects of implementing process changes. This latter point is particularly valuable, as it allows for several alternatives to be studied in a virtual setting before committing resources to making a change in the field. The decision to develop OR models has gained tremendous support from the Site's stakeholders and the U.S. Department of Energy (DOE) management, and has prompted the use of the tool to support additional internal and external initiatives. Recently, an initiative was proposed to use the models to help identify and provide quantitative backing for risks and opportunities for the TOC. This application of OR could not only help inform how the TOC manages its risks (e.g. quantities and types of spare parts), but could also help drive process improvements whose benefits might otherwise be hard to quantify. The models have also been used to drive the TOC's cloud computing, artificial intelligence (AI), and machine learning (ML) initiatives. These initiatives will not only improve the ability of the TOC to more rapidly respond to the needs of its customers, but it will also aid in the ability of the TOC to analyze and improve the processes it studies. Partnership with two external software development and consulting companies (Lanner and Ynformed) has furthered not only the application of AI and ML within the TOC, but has also spurred the development of new/improved software tools and platforms used by the companies. These partnerships have proven to be mutually beneficial and productive, and have set a precedent for the types of gains that can be made by exploring such options. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2011

Reliability and Maintainability Engineering - A Major Driver for Safety and Affordability

The United States National Aeronautics and Space Administration (NASA) is in the midst of an effort to design and build a safe and affordable heavy lift vehicle to go to the moon and beyond. To achieve that, NASA is seeking more innovative and efficient approaches to reduce cost while maintaining an acceptable level of safety and mission success. One area that has the potential to contribute significantly to achieving NASA safety and affordability goals is Reliability and Maintainability (R&M) engineering. Inadequate reliability or failure of critical safety items may directly jeopardize the safety of the user(s) and result in a loss of life. Inadequate reliability of equipment may directly jeopardize mission success. Systems designed to be more reliable (fewer failures) and maintainable (fewer resources needed) can lower the total life cycle cost. The Department of Defense (DOD) and industry experience has shown that optimized and adequate levels of R&M are critical for achieving a high level of safety and mission success, and low sustainment cost. Also, lessons learned from the Space Shuttle program clearly demonstrated the importance of R&M engineering in designing and operating safe and affordable launch systems. The Challenger and Columbia accidents are examples of the severe impact of design unreliability and process induced failures on system safety and mission success. These accidents demonstrated the criticality of reliability engineering in understanding component failure mechanisms and integrated system failures across the system elements interfaces. Experience from the shuttle program also shows that insufficient Reliability, Maintainability, and Supportability (RMS) engineering analyses upfront in the design phase can significantly increase the sustainment cost and, thereby, the total life cycle cost. Emphasis on RMS during the design phase is critical for identifying the design features and characteristics needed for time efficient processing, improved operational availability, and optimized maintenance and logistic support infrastructure. This paper discusses the role of R&M in a program acquisition phase and the potential impact of R&M on safety, mission success, operational availability, and affordability. This includes discussion of the R&M elements that need to be addressed and the R&M analyses that need to be performed in order to support a safe and affordable system design. The paper also provides some lessons learned from the Space Shuttle program on the impact of R&M on safety and affordability.

Safie, Fayssal M.↗
DOE OSTI2024

Impact of Electric Vehicle Charging Station Reliability, Resilience, and Location on Electric Vehicle Adoption

While the majority of electric vehicle (EV) charging events in the United States occur at home, issues with public charging stations are consistently found to be a top reason that potential EV buyers do not purchase an EV, demonstrating that both EVSE reliability and availability impacts EV adoption. This report explores multiple parameters that impact EVSE reliability and deployment, which in turn impact EV sales. These include extreme weather, codes and standards, region (urban vs. rural), and grid network type. Grid reliability was not found to impact EV adoption. The relationships between EV station reliability, station resilience, grid resilience, and EV adoption are largely outside the scope of the National Renewable Energy Laboratory's (NREL's) Automotive Deployment Options Projection Tool (ADOPT) and other vehicle adoption models, so the methodology of this report is varied. Section 2 sets the baseline for infrastructure reliability, user satisfaction, and maintenance practices. Section 3 explores the ways that electric vehicle supply equipment (EVSE) reliability impacts the relationship between EVSE and EV adoption. Section 4 shows how geographical categories such as urban, rural, large grid, off-grid, or microgrid can be helpful in EVSE deployment strategies, as well as how the relationship between EVSE and EV adoption differs among these categories. Section 5 investigates the impacts of grid reliability and infrastructure resilience on EV adoption. Finally, Section 6 reverses the perspective to examine the impact that EVs and EVSE have on grid resilience and reliability. As recent funding initiatives result in an expansion of public chargers across the United States, as well as an increase in the uptime of existing chargers, EV adoption will likely grow.

33 ADVANCED PROPULSION SYSTEMS↗