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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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This paper is to describe the engineering challenges in the surface mobility of the Mars 2020 Rover mission that are considered in the landing site selection process, introduce new automated traversability analysis capabilities, and present the preliminary analysis results for top candidate landing sites.
The NEPP FY07 Sensor Technology Commercial Sensor Survey task is geared toward benefiting future NASA space missions with low-cost, short-duty-cycle, visible imaging needs. Such applications could include imaging for educational outreach purposes or short surveys of spacecraft, planetary, or lunar surfaces. Under the task, inexpensive commercial grade sensors (e.g., CMOS-based “camera on a chip” systems) have been surveyed and selected for ionizing dose and displacement damage tolerance testing. Only inexpensive, commercial imagers with potential for use in low-duty-cycle space exploration applications have been considered; the task does not address high-cost science grade imagers or hardened technologies. The selected sensors had to meet selection criteria geared toward supporting small, low-mass cameras that produce good resolution color images. This document discusses the selection process.
We have developed a comprehensive model of the Mars 2020 rover surface mission used to identify and evaluate mission productivity and operability challenges and opportunities. The surface mission performance model combines many aspects of rover design, operations approach, system behaviors, and mission constraints into an integrated model of surface mission performance. The surface mission model applies monte-carlo methodologies in order to investigate the key sources of mission performance variability and their effects with respect to overall mission performance. Our modeling efforts aims to investigate and inform engineering design and development efforts, as well as the landing site selection process led by the Mars science community. We believe that an integrated mission performance model such as this is important to aligning engineering and science efforts across the project.
For spacecraft applications requiring active refrigeration, exported vibrations from a cryocooler can be a concern. One approach to minimizing the vibrations transmitted from cryocoolers to the spacecraft is to mount them on mechanical isolators. Many commercial off-theshelf (COTS) mechanical isolators exist and have been characterized at room temperature for ground applications. However, the space environment presents challenges that complicate the selection process. Mechanical isolators in space must be made of materials that can withstand harsh radiation environments. Future instruments, such as the Mapping Imaging Spectrometer for Europa (MISE) on the Europa Clipper mission, are considering operating cryocoolers with low heat rejection temperatures and mounting them on mechanical isolators. However, the performance of many simple, traditional mechanical isolators at low temperatures is unknown. This paper describes the testing and results of various mechanical isolators able to withstand harsh radiation between 200 K and 300 K. The transmissibility of wire rope type isolators showed very little temperature dependence up to ~500 Hz. On the other hand, the transmissibility of silicone gel was strongly dependent on temperature as the material had an abrupt change in stiffness near its solid-solid phase change. Custom titanium flexures showed the most promise with a maximum transmissibility of 0.04 above 500 Hz and no expected temperature dependence.
Since 1960s NASA’s missions have spanned the entire solar system, from Apollo to Jupiter entry ~50 km/s. Ablative TPS has been critical to the success. NASA’s missions will continue to be innovative, one-of-a kind and at the same time, competed mission selection process requires technology readiness to be high to ensure cost and risks are better understood. If missions require new TPS technology, it takes a decade and significant resources to develop them. Competitive proposal tend to use existing ablative TPS. Sustainability of ablative TPS is then essential. This talk will focus on approaches to address the future challenges.
NASA’s Human Research Program oversees the Team Risk (i.e., Risk of Performance and Behavioral Health Decrements due to Inadequate Cooperation, Coordination, Communication and Psychosocial Adaptation within a Team). Research in this area informs all aspects of an astronaut’s career, from hiring to training to mission support, and works to address new challenges related to lunar and Mars missions. NASA’s astronaut selection process creates an astronaut corps of highly qualified, team-oriented individuals, which allows mission planners much flexibility in composing small crews for specific missions. These crews are further developed and supported through extensive training, including team skills training, and countermeasures available to the crew throughout the mission. However, in the high consequence environment of long-duration missions, team composition is complex and is not a one-time concern to be addressed pre-mission. Team factors such as team cohesion, dyadic relationships, and shared team cognition are likely to change dynamically in response to each interaction and event experienced by the individuals and the team as a whole. Thus, monitoring and optimizing team composition at a more micro level (e.g., per task) is one way to support team functioning and performance. Spaceflight teams research also includes the multi-team system of Mission Control and coordination between space-to-ground, adding another avenue in which risk might be introduced, particularly under exploration missions that experience significant communication delays. Spaceflight teams research has recently experienced a concentrated flurry of analog research over the past decade, shedding light on the many unique challenges and potential solutions to mitigate the team risk in long-duration exploration missions. However, questions still remain about how to, for example, create unobtrusive operational measures and how to advance interdisciplinary teams research and countermeasure development. We present an overview of the challenges facing teams in space, our current knowledge, and the next steps for research and spaceflight operations.
Overarching goal: Create Climatological Lidar Ratio Maps for CALIPSO - Since CALIPSO is an elastic backscatter lidar, it is necessary to select a priori aerosol lidar ratios prior to computing extinction profiles. - Presently, the CALIPSO lidar ratio selection process uses a single lidar ratio for each of the 7 CALIPSO aerosol types in the troposphere. - Consequently, regional and seasonal variability of the lidar ratio is very limited in the present CALIPSO algorithm. - Here, we describe an approach for creating new climatological lidar ratio maps for each of the CALIPSO aerosol types using MODIS-CALIPSO constrained retrievals and global model simulations. - The purpose is to eventually replace the seven single-valued lidar ratios for the CALIPSO types with latitude- and longitude-dependent maps for each of the seven types.
- After 16+ years, the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission will soon retire. - Narrow window of opportunity exists to improve quality of CALIPSO aerosol retrievals by advancing knowledge of aerosol lidar ratios for different aerosol types; - For CALIOP, the elastic backscatter lidar aboard CALIPSO, an aerosol lidar ratio (i.e., extinction-to-backscatter ratio) is generally assumed to retrieve vertical profiles of aerosol extinction and subsequently column-integrated aerosol optical depth (AOD). - Current CALIPSO lidar ratio selection process uses a single lidar ratio for each of the 7 CALIPSO tropospheric aerosol types, with large uncertainties for most aerosol types. Goal of this study: creation of regional and seasonal climatological lidar ratio maps for marine aerosols by leveraging passive aerosol retrievals (MODIS) and global model simulations (GEOS/GOGART).
The availability of fresh produce during longer-duration spaceflight missions is being explored as a countermeasure for human biobehavioral health and performance, including how fresh fruits and vegetables can supplement the crew diet with nutrients that are predicted to become deficient throughout the missions. Crop production in the Veggie and Advanced Plant Habitat vegetable production chambers on the International Space Station (ISS) have tested pick-and-eat crops in spaceflight. However, the limited plant cultivation volume of these chambers has restricted the sample sizes and biomass allocated for nutrition assessment. To gain a better understanding of the nutrient composition of pick-and-eat crops, leafy greens and fruiting plants were grown in the EDEN ISS plant cultivation facility near the German Neumayer Station III in Antarctica from March 2021 to January 2022. Target crops for nutrition sampling aligned with cultivars grown in spaceflight, including ‘Outredgeous’ red romaine lettuce, Mizuna mustard, ‘Red Robin’ dwarf cherry tomato, and NuMex ‘Española Improved’ chili pepper. Plants subsamples were taken at harvest; in the event of multiple harvests from the same plants, subsamples were taken at both the first and final harvests. ‘Outredgeous’ and Mizuna were also grown multiple times throughout the year, allowing multiple grow-outs to be analyzed for potential effects across the growing season. Subsamples were first weighed for fresh mass, dried in a dedicated oven at 70°C for 96 h, weighed again, and stored in air-tight containers inside Neumayer Station III. At the beginning of 2022, the samples were shipped to NASA’s Kennedy Space Center, where they are currently being analyzed with ion chromatography for nutrients of interest in the astronaut diet, including calcium, iron, magnesium, and potassium. This study aims to increase our understanding of how the crops that have successfully grown on the ISS can supplement the crew diet, as well as how other factors like plant age and the number of days the facility has been in operation may impact nutrient concentrations. Such findings can improve the crop selection process and how pick-and-eat crops are cultivated during spaceflight missions.
The availability of fresh produce during longer-duration spaceflight missions is being explored as a countermeasure for human biobehavioral health and performance, including how fresh fruits and vegetables can supplement the crew diet with nutrients that are predicted to become deficient throughout the missions. Crop production in the Veggie and Advanced Plant Habitat vegetable production chambers on the International Space Station (ISS) have tested pick-and-eat crops in spaceflight. However, the limited plant cultivation volume of these chambers has restricted the sample sizes and biomass allocated for nutrition assessment. To gain a better understanding of the nutrient composition of pick-and-eat crops, leafy greens and fruiting plants were grown in the EDEN ISS plant cultivation facility near the German Neumayer Station III in Antarctica from March 2021 to January 2022. Target crops for nutrition sampling aligned with cultivars grown in spaceflight, including ‘Outredgeous’ red romaine lettuce, Mizuna mustard, ‘Red Robin’ dwarf cherry tomato, and NuMex ‘Española Improved’ chili pepper. Plants subsamples were taken at harvest; in the event of multiple harvests from the same plants, subsamples were taken at both the first and final harvests. ‘Outredgeous’ and Mizuna were also grown multiple times throughout the year, allowing multiple grow-outs to be analyzed for potential effects across the growing season. Subsamples were first weighed for fresh mass, dried in a dedicated oven at 70°C for 96 h, weighed again, and stored in air-tight containers inside Neumayer Station III. At the beginning of 2022, the samples were shipped to NASA’s Kennedy Space Center, where they are currently being analyzed with ion chromatography for nutrients of interest in the astronaut diet, including calcium, iron, magnesium, and potassium. This study aims to increase our understanding of how the crops that have successfully grown on the ISS can supplement the crew diet, as well as how other factors like plant age and the number of days the facility has been in operation may impact nutrient concentrations. Such findings can improve the crop selection process and how pick-and-eat crops are cultivated during spaceflight missions.
Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.
A method for the manufacture of a three-dimensional object using a refractory matrix material is provided. The method includes the additive manufacture of a green body from a powder-based refractory matrix material followed by densification via chemical vapor infiltration (CVI). The refractory matrix material can be a refractory ceramic (e.g., silicon carbide, zirconium carbide, or graphite) or a refractory metal (e.g., molybdenum or tungsten). In one embodiment, the matrix material is deposited according to a binder-jet printing process to produce a green body having a complex geometry. The CVI process increases its density, provides a hermetic seal, and yields an object with mechanical integrity. The residual binder content dissociates and is removed from the green body prior to the start of the CVI process as temperatures increase in the CVI reactor. The CVI process selective deposits a fully dense coating on all internal and external surfaces of the finished object.
As the use of renewable energy resources increases within charging infrastructures, the risk that charging an additional load within the charging infrastructure will create a violation of the applicable grid code also increases. In an embodiment, a charging location is selected for an incoming load based on a load flow analysis, to thereby mitigate the risk of a violation. This selection process may also account for the charging schedule of the load and the capacity of available charging stations (e.g., fast charging vs. slow charging).
A method for the manufacture of a three-dimensional object using a refractory matrix material is provided. The method includes the additive manufacture of a green body from a powder-based refractory matrix material followed by densification via chemical vapor infiltration (CVI). The refractory matrix material can be a refractory ceramic (e.g., silicon carbide, zirconium carbide, or graphite) or a refractory metal (e.g., molybdenum or tungsten). In one embodiment, the matrix material is deposited according to a binder-jet printing process to produce a green body having a complex geometry. The CVI process increases its density, provides a hermetic seal, and yields an object with mechanical integrity. The residual binder content dissociates and is removed from the green body prior to the start of the CVI process as temperatures increase in the CVI reactor. The CVI process selective deposits a fully dense coating on all internal and external surfaces of the finished object.
The Jaynes-Cummings (JC) interaction-the coherent exchange of excitations between a two-level system and a harmonic oscillator-is one of the fundamental interactions of quantum optics, realized across platforms such as cavity quantum electrodynamics, trapped ions, mechanical resonators, and superconducting circuits. Although JC interactions and qubit rotations form a universal gate set for oscillator control, practical implementations have not been demonstrated. Here we develop and experimentally demonstrate universal JC-based oscillator control by compiling arbitrary unitary gates into sequences of JC interactions and qubit rotations. In our experiment, the oscillator is realized using a mode of a high quality factor microwave cavity and the ancilla qubit using a superconducting transmon circuit, with the JC interaction implemented by a sideband interaction enabled by the Josephson nonlinearity. The native gates are constructed to be closed below a chosen cutoff photon number, encoding a qudit with suppressed leakage errors, while ancilla relaxation errors are detectable. We further find that the dispersive shift serves as a compilation resource that reduces circuit depths. We demonstrate universal qudit control and implement a single-qutrit gate set with a mean post-selected process fidelity of 96%, as well as ququart and ququint shift gates. These results establish Jaynes-Cummings control as a practical route to universal oscillator control, enabling programmable bosonic processors across a variety of quantum platforms.
Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs).
The powder bed-based additive manufacturing (AM) process contains uncertainties in the powder spreading process and powder bed quality, leading to problems in repeatability and quality of the additively manufactured parts. This work focuses on identifying the uncertainty induced by particle size distribution (PSD) on powder flowability and the laser melting process, using Ti6Al4V as a model material. The flowability test results show that the effect of PSDs on flowability is not linear, rather the PSDs near dense packing ratios cause significant reductions in flowability (indicated by the increase in the avalanche angle and break energy of the powders measured by a revolution powder analyzer). The effects of PSDs on the selective laser melting (SLM) process are identified by using in-situ high-speed X-ray imaging to observe the melt pool dynamics during the melting process. The results show that the powder beds made of powders with dense packing ratios exhibit larger build height during laser melting. The effects of PSD with efficient packing on powder flowability and selective laser melting process revealed in this work are important for understanding process uncertainties induced by feedstock powders and for designing mitigation approaches.
The trend in the modern global economy towards free market policies has motivated companies to use rapid prototyping technologies to not only reduce product development cycle time but also to maintain their competitive edge. A rapid prototyping technology is one which combines computer aided design with computer controlled tracking of focussed high energy source (eg. lasers, heat) on modern ceramic powders, metallic powders, plastics or photosensitive liquid resins in order to produce prototypes or models. At present, except for the process of shape melting, most rapid prototyping processes generate products that are only dimensionally similar to those of the desired end product. There is an urgent need, therefore, to enhance the understanding of the characteristics of these processes in order to realize their potential for production. Currently, the commercial market is dominated by four rapid prototyping processes, namely selective laser sintering, stereolithography, fused deposition modelling and laminated object manufacturing. This phase of the research has focussed on the selective laser sintering and stereolithography rapid prototyping processes. A theoretical model for these processes is under development. Different rapid prototyping sites supplied test specimens (based on ASTM 638-84, Type I) that have been measured and tested to provide a data base on surface finish, dimensional variation and ultimate tensile strength. Further plans call for developing and verifying the theoretical models by carefully designed experiments. This will be a joint effort between NASA and other prototyping centers to generate a larger database, thus encouraging more widespread usage by product designers.