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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 253 records · Page 14

Wholesale Electricity Market Design to Support Resource Adequacy

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

agent based modeling

A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification

Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.

biological databases

Back Propagation Neural Networks for Predicting Ultimate Strengths of Unidirectional Graphite/Epoxy Tensile Specimens

The research presented herein demonstrates the feasibility of predicting ultimate strengths in simple composite structures through a neural network analysis of their acoustic emission (AE) amplitude distribution data. A series of eleven ASTM D-3039 unidirectional graphite/epoxy tensile samples were loaded to failure to generate the amplitude distributions for this analysis. A back propagation neural network was trained to correlate the AE amplitude distribution signatures generated during the first 25% of loading with the ultimate strengths of the samples. The network was trained using two sets of inputs: (1) the statistical parameters obtained from a Weibull distribution fit of the amplitude distribution data, and (2) the event frequency (amplitude) distribution itself. The neural networks were able to predict ultimate strengths with a worst case error of -8.99% for the Weibull modeled amplitude distribution data and 3.74% when the amplitude distribution itself was used to train the network. The principal reason for the improved prediction capability of the latter technique lies in the ability of the neural network to extract subtle features from within the amplitude distribution.

Walker, James L.

Short-Term Probabilistic Solar Forecasting via Reinforcement Learning over ECMWF

In this paper, we present an innovative reinforcement learning approach for short-term solar forecasting, leveraging data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The methodology begins with the application of the System Advisor Model (SAM) to transform various ECMWF numerical weather prediction members into predictive photovoltaic power generation. To enhance the precision of deterministic forecasting, we introduce a dynamic model selection algorithm based on Q-learning. This algorithm dynamically identifies and utilizes the most accurate ensemble member for forecasting purposes. Furthermore, we employ a support vector regression surrogate model with a Gaussian distribution to generate probabilistic forecasts, providing a holistic view of solar energy generation uncertainty. To expedite the training process and make it more practical for real-world applications, we integrate a rolling update workflow. This innovative workflow reduces the training period from months to a mere 19 days, making our method highly efficient. Numerical results of the case study show that in comparison to benchmark models, the proposed method improves the deterministic and probabilistic solar forecasting accuracy by up to 40.84% and 48.42%, respectively.

ensemble forecasting

1988 Delaware Valley Regional Planning Commission Household Travel Survey

The Delaware Valley Regional Planning Commission conducted household travel surveys in 1988 for the Delaware Valley region of Pennsylvania, which consists of Bucks, Chester, Delaware, Montgomery, and Philadelphia counties. The home interview travel survey was intended to measure the travel habits of area residents, and it generated needed information on trip generation rates, trip distribution, and model choice. This information was used for model calibration and validation on the trip generation, trip distribution, and model split models. The data includes demographic and socioeconomic details, as well as travel patterns, for 1,567 households. A total of 5,733 people reported a total of 18,899 trips. The survey was conducted on a weekday, Monday through Friday, and only ten survey locations contained weekend day travel.

1Hz data

The EOSDIS Version 0 Distributed Active Archive Center for physical oceanography and air-sea interaction

The Distributed Active Archive Center (DAAC) at the Jet Propulsion Laboratory will support scientists specializing in physical oceanography and air-sea interaction. As part of the NASA Earth Observing System Data and Information System Version 0 the DAAC will build on existing capabilities to provide services for data product generation, archiving, distribution and management of information about data. To meet scientist's immediate needs for data, existing data sets from missions such as Seasat, Geosat, the NOAA series of satellites and the Global Positioning Satellite system will be distributed to investigators upon request. In 1992, ocean topography, wave and surface roughness data from the Topex/Poseidon radar altimeter mission will be archived and distributed. New data products will be derived from Topex/Poseidon and other sensor systems based on recommendations of the science community. In 1995, ocean wind field measurements from the NASA Scatterometer will be supported by the DAAC.

Hilland, Jeffrey E.

Towards a data-driven model of hadronization using normalizing flows

We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing flows, termed MAGIC, that improves the agreement between simulated and experimental distributions of high-level (macroscopic) observables by adjusting single-emission (microscopic) dynamics. Our results constitute an important step toward realizing a machine-learning based model of hadronization that utilizes experimental data during training. Finally, we demonstrate how a Bayesian extension to this normalizing-flow architecture can be used to provide analysis of statistical and modeling uncertainties on the generated observable distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Moisture analysis from radiosonde and microwave spectrometer data

A method for analysis of the horizontal and vertical distributions of the moisture field utilizing satellite, upper air and surface data is proposed in this paper. A brief overview of the microwave sensors on board Nimbus 5 and 6 is also presented. A technique is provided utilizing the radiosonde data sets to calibrate the satellite field of total precipitable water. Next, the calibrated satellite-derived field is utilized along with ship and coastal reports of moisture, and a vertical structure function to generate vertical distribution of moisture and thus provide a mapping of specific humidity at several levels in the troposphere. Utilizing these procedures, analyses for several case studies were performed. The resultant maps show detailed distribution of specific humidity along with some interesting climatological features. A reasonable acceptance of the available aerological data sets by the analysis scheme is demonstrated.

Haydu, K. J.

High Pressure X-Ray Diffraction Studies of Nanocrystalline Materials

Experimental evidence obtained for a variety of nanocrystalline materials suggest that the crystallographic structure of a very small size particle deviates from that in the bulk crystals. In this paper we show the effect of the surface of nanocrystals on their structure by the analysis of generation and distribution of macro- and micro-strains at high pressures and their dependence on the grain size in nanocrystalline powders of Sic. We studied the structure of Sic nanocrystals by in-situ high-pressure powder diffraction technique using synchrotron and neutron sources and hydrostatic or isostatic pressure conditions. The diffraction measurements were done in HASYLAB at DESY using a Diamond Anvil Cell (DAC) in the energy dispersive geometry in the diffraction vector range up to 3.5 - 4/A and under pressures up to 50 GPa at room temperature. In-situ high pressure neutron diffraction measurements were done at LANSCE in Los Alamos National Laboratory using the HIPD and HIPPO diffractometers with the Paris-Edinburgh and TAP-98 cells, respectively, in the diffraction vector range up to 26 Examination of the response of the material to external stresses requires nonstandard methodology of the materials characterization and description. Although every diffraction pattern contains a complete information on macro- and micro-strains, a high pressure experiment can reveal only those factors which contribute to the characteristic diffraction patterns of the crystalline phases present in the sample. The elastic properties of powders with the grain size from several nm to micrometers were examined using three methodologies: (l), the analysis of positions and widths of individual Bragg reflections (used for calculating macro- and micro-strains generated during densification) [I], (2). the analysis of the dependence of the experimental apparent lattice parameter, alp, on the diffraction vector Q [2], and (3), the atomic Pair Distribution Function (PDF) technique [3]. The results of our studies show, that Sic nanocrystals have the features of two phases, each with its distinct elastic properties. and under pressures up to 8 GPa.

Palosz, B.

Integrity of Ceramic Parts Predicted When Loads and Temperatures Fluctuate Over Time

Brittle materials are being used, and being considered for use, for a wide variety of high performance applications that operate in harsh environments, including static and rotating turbine parts for unmanned aerial vehicles, auxiliary power units, and distributed power generation. Other applications include thermal protection systems, dental prosthetics, fuel cells, oxygen transport membranes, radomes, and microelectromechanical systems (MEMS). In order for these high-technology ceramics to be used successfully for structural applications that push the envelope of materials capabilities, design engineers must consider that brittle materials are designed and analyzed differently than metallic materials. Unlike ductile metals, brittle materials display a stochastic strength response because of the combination of low fracture toughness and the random nature of the size, orientation, and distribution of inherent microscopic flaws. This plus the fact that the strength of a component under load may degrade over time because of slow crack growth means that a probabilistic-based life-prediction methodology must be used when the tradeoffs of failure probability, performance, and useful life are being optimized. The CARES/Life code (which was developed at the NASA Glenn Research Center) predicts the probability of ceramic components failing from spontaneous catastrophic rupture when these components are subjected to multiaxial loading and slow crack growth conditions. Enhancements to CARES/Life now allow for the component survival probability to be calculated when loading and temperature vary over time.

Nemeth, Noel N.

IUE observations of the M dwarfs CM Draconis and Rossiter 137 B - Magnetic activity at saturated levels

IUE observations of two active M dwarfs with known rotation rate or age and presumed to be almost totally convective are presented. The first of these stars, CM Draconis (Gl 630.1), is an old Population II binary with its components in tidally induced rapid rotation (P = 1.27 d, dM 4 + dM 4). The other one, Rossiter 137 B, forms with HD 36705 (AB Dor) a visual pair of young active stars. The activity of CM Dra is due to the forced rotation in a close binary, while Rst 137 B is assumed to rotate fast enough to generate its magnetica activity. These results are compared with those for M dwarfs, particularly AU Mic and YZ CMi, that have known rotational periods and measured ultraviolet emission line fluxes. The chromospheric-coronal saturation levels of cool dwarfs between 0.3 less than B-V less than 1.6 is determined. It is found that saturated F stars have stronger chromospheres than saturated M stars, but the opposite is true for the corona. Results of these observations seem to favor a rotation-dependent distributed dynamo generating magnetic flux in totally convective stars.

Vilhu, O.

A stochastic precipitation disaggregation scheme for GCM applications

In the surface hydrologic parameterization of general circulation models (GCMs), it is commonly assumed that the precipitation processes are homogeneous over a GCM grid square and that the precipitation intensity is uniformly distributed. Based on evidence that the spatial distribution of precipitation within a GCM grid square is crucial for the land surface hydrology parameterization, a few researchers have explored the impacts of assuming that the precipitation is exponentially distributed. This paper explores the suitability of the aforementioned assumptions. First, a statistical analysis is conducted of historical precipitation data for three GCM grids in different regions of the United States. The analysis suggests that neither the uniform nor the exponential distribution assumption may be suitable at the GCM grid scale and, that instead, the spatial variability in precipitation is characterized by statistical patterns that are inhomogeneous. These patterns vary from grid to grid and are induced by the interaction between atmospheric conditions and various land surface characteristics, such as topographical features, surface properties, etc. Within the same grid square, however, the statistical patterns are generally constant from year to year. Based on this analysis, a computationally viable (i.e., usable with GCMs) stochastic precipitation disaggregation scheme that utilizes these stable statistical patterns is proposed. The method was used to generate spatially distributed hourly rainfall for a summer season in the southwestern region of the continental United States. Analysis of the results shows that the methodology preserves the seasonal characteristics of spatial variability in precipitation that is observed in the long-term historical data.

Gao, Xiaogang

Space Transformation -- Localizing the Remote and Connecting the Isolated

In motivating the Space Transformation theme for this year’s 4S symposium, the organizers provided the following context, “Transformation of economies are driven by a change in values and accelerated by new technologies.” These words rang particularly true when I read them at the beginning of the holiday season. Like so many others, I was in the early phases of my Christmas shopping procrastination campaign, and I’d just been reflecting on how Amazon Prime was the transformational tool I’d been waiting for. Basic limiting principles of time and space, supply and demand, were all but erased by the Amazon Prime phenomenon. Coupled with emerging 3D printing and other adaptive manufacturing technologies, a transformation from deliberate planning to “think it … have it” had occurred, empowering me to procrastinate longer than I’d ever dreamed possible. The organizers went on to ponder, “Will space transformation also affect society?”, just as our team at the Air Force Research Lab’s (AFRL) Center for Rapid Innovation (CRI) were working alongside partners within our larger Integrated Capabilities Directorate, NASA’s Flight Opportunities and Small Spacecraft Technology programs, and DARPA’s Luna-10 program to develop technologies and execute demonstration missions that leverage the space domain to genuinely connect even the most remote and austere domains on the timeline of need. Picking apart the miracle that is Amazon prime, where does the model fail, and why? More relevantly to the theme of this year’s symposium, how can the space domain be used to overcome its limitations and minimize its weaknesses? Perhaps it is best assessed in the context of Use Cases. What are the Amazon delivery cost, schedule, and cargo limiters to the Amundsen-Scott South Pole Research Station, or the Lunar South Pole Research Station? This paper will explore enabling infrastructure that allows Amazon prime to thrive and assess the transformational enabling technologies that would be necessary to extend that miracle to the truly remote or the truly austere. Localizing the Remote • First, it will evaluate the ability of the on-going AFRL Rocket Cargo and Space Initiatives Ringside Seats systems, coupled with Astrobotic’s Xodiak and Xogdor capabilities, developed to support the NASA Flight Opportunities Program (FOP), to supply orbital/suborbital delivery to both improved and austere sites on the Earth and Moon. • Then, it will add the surface terminal distribution leg, with an examination of Lunar Outpost’s Mobile Autonomous Prospecting Platform (MAPP), equipped with Mobile Autonomous Robotic Swarm (MARS) software, and Intuitive Machine’s Hopper, developed with support of AFRL and NASA’s Commercial Lunar Payload Services (CLPS) program. Connecting the Isolated From there, it will focus on the destination, asking what implied destination services are required to support highly assured autonomous delivery. • Specifically, it will highlight Astrobotic’s Skymage mesh-networked publish and subscribe communication and navigation service, as well as AFRL’s on-going developments of radioisotope and reactor nuclear-sourced thermoelectric power generation and distribution systems under development under the Joint Emergent Technology Supplying On-orbit Nuclear Power (JETSON) program by Lockheed Martin, Westinghouse, Intuitive Machines, and Zeno Power, to provide the power service to locations well off the grid. • Finally, the paper will connect to the “human machine”. What connects the remote or in-situ human consumer to the remote domain? What connects the diverse international government and commercial services to each other? The former will focus on AFRL’s OraCloud feeding their Space Defense Control and Characterization System (SDCCS) and Lunar Station’s MoonHacker systems, while the latter will focus on the BlueHalo/Tensor LunX Technology Platform for the Cislunar Commodity Marketplace. In 1984, Krafft Ehricke famously remarked that, “If God wanted man to become a spacefaring species, He would have given man a Moon.” This paper is not about the Moon, but is about humans as a spacefaring species, shedding the pesky land/air limitations of the Amazon Prime model … so that we can all live a procrastinator’s “think it … have it” existence.

Charles Finley

Advanced Semi-Supervised Learning with Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION

Advanced Semi-Supervised Learning With Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION

Uncrewed Lunar Surface Operations and Support Activities

Sustained human presence on the surface of the Moon and future missions to Mars require increased independence from surface crews and Earth-based mission control to operate efficiently, safely, and reliably. The time for surface crews to perform tasks will be limited. Extravehicular activities by surface personnel are burdensome and time-consuming, even when a continuous human presence on the surface occurs. Identifying and balancing human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle will be essential to achieve mission objectives. Among these objectives are attaining a sustained human presence, improving performance and mission effectiveness, reducing operations and maintenance (O&M) costs, and ensuring operations that are robust to communication delays. To achieve these objectives, an operational shift toward increased automation and autonomy with less reliance on humans is needed. Uncrewed lunar surface operations and support activities occur when surface crews are not present or are independent of surface crew timeline activities requiring no surface crew oversight or intervention. These uncrewed surface opportunities can also be planned to minimize crew workload that avoids routine maintenance and support tasks, thus maximizing crew exploration time. Uncrewed preparations such as staging and prepositioning equipment and materials before the crew arrives could improve crew task efficiency. Additional opportunities exist to conduct uncrewed science, exploration, and utilization. Uncrewed surface architecture functions can include science and exploration; habitation; launch and landing support; surface communication and navigation; surface power generation and distribution; human surface mobility; lifting, handling, manipulating; excavation, construction, and site preparation; logistics management; maintenance and repair; surface resource utilization; integrated site operations and shared support services (e.g., site scheduling/prioritization, dust mitigation/contamination control, and surface safety). Early robotic lunar surface campaigns will provide information on the availability of resources, such as oxygen and water, and demonstrate surface-based technologies. After the Artemis III human lunar return mission, a series of landers will deliver surface systems, cargo, supplies, science packages, spare parts, and commodities. A balance of crewed and uncrewed surface operations will enable a sustained lunar surface presence at the South Pole of the Moon at a site that will be known as the Artemis Base Camp (ABC). It is envisioned that base camp operations on and around the Moon will then help prepare for the mission durations and activities needed to support the first human mission to Mars. Before long-duration crew missions to the base camp can occur, the necessary surface infrastructure will be pre-deployed and verified operational. Surface assets will be teleoperated and remotely managed from Earth. Additionally, robotic and short-duration crewed missions to the ABC will ensure the site’s merit to achieve long-term science objectives, availability of usable resources, and that terrain, seasonal variations, and illumination conditions are acceptable. ABC will consist of different areas where specific functions and services are rendered, including: • Launch and Landing Area • Habitation Area • Power Production Area • Resource Areas Launch and Landing Area—The launch and landing area will support associated functions for the arrival and departure of vehicles, such as crewed landing and ascent and uncrewed cargo deliveries and offloading. It will evolve from an unimproved site at the beginning of the exploration campaign to a more sustainable landing and launch area that can support repeated arrivals and departures. Initial uncrewed Lunar Terrain Vehicle (LTV) surface operations may include emplacement of navigation beacons and communication equipment, real-time video and photography of landing/liftoff events, and element repositioning, such as portable utility power (PUP) (applicable for other landed assets at other areas). Site preparations, such as surface leveling, soil compaction, and berm/path construction, may be needed for a more sustainable launch and landing area capable of accommodating vehicles that are increasingly more reusable and reduce the effects of plume surface interactions and ejecta impacts on nearby surface assets. During the ABC missions, cargo and logistics will be delivered to the lunar surface via robotic cargo landers before the crew arrives. These shipments, which can arrive in pressurized logistics carriers, will deliver the logistics necessary to support a crewed mission and include items such as food, water, equipment spares, etc. Providing the capability to retrieve, offload, and transport the logistics closer to the ABC site before the arrival of the crew will increase the overall efficiency of crew operations once they arrive. In the sustained phase of exploration, other supporting services may be needed, such as lander propellant servicing, surface power services, commodity refreshes, and additional inspection, maintenance, and repair capabilities, to sustain a cadence of extended personnel stays and cargo arrivals and departures. Habitation Area—Uncrewed support to surface habitation could involve supporting activation and pre-entry operations of the habitat while the crew is in orbit at the Gateway outpost preparing for a surface landing. Surface Habitat (SH) uncrewed operations may include bringing the cabin environment to a habitable temperature and air mix and activating other critical crew support systems. Potential crop production uncrewed tasks in the SH could also include autonomous watering and tending. Additionally, when the crew departs, the SH enters dormancy for the long period of uncrewed operation. A logistical staging area could also be collocated near the SH. If so, staging operations for crew supplies, waste re-location, and recycling operations may be opportunities for uncrewed operations. Power Production Area—The Fission Surface Power (FSP) element and its supporting distribution equipment provide power to surface elements as needed across the ABC to supplement day-to-day operations and survive lunar nights. Uncrewed support of this power system includes any initial LTV-assisted deployments of cables and other distributed equipment, associated electrical connections, and system testing and activation operations. Robotically performing some inspections, maintenance, or repair tasks on the power distribution equipment could reduce the surface crew workload. Resource Area— Uncrewed resource prospecting, mapping, and characterizing possible resource sites is likely to be time-consuming and represents an opportunity for uncrewed operations between crewed missions. Uncrewed mobile equipment operations will be needed in the extreme environments of permanently shadowed locations where resource extractions occur. As In-Situ Resource Utilization (ISRU) pilot plant operations begin, uncrewed surface support activities with available mobile and portable assets (LTV, PUP, etc.) will better support these operations. Any produced commodities can be stored at a centralized storage location for future use. Also associated with these operations is the use of mobile robotic excavators for resource acquisition and robotic/autonomous regolith processing. The waste tailings generated during excavation and regolith processing would also need to be transported and deposited at a dedicated location. Surface assets will continue operating between crew visits to maintain surface capabilities, conduct lunar surface science, technology demonstrations, and public outreach opportunities. Additionally, certain sustaining tasks that would consume valuable crew time could be performed before crew arrival, or after their departure. This capability may offer more affordable options to construct, activate, test, and maintain a broad set of surface assets. Telerobotically operated human surface mobility systems, such as the LTV and Pressurized Rover (PR), can be utilized for various tasks. Surface environmental conditions pose a distinct challenge for all these activities. Surface illumination and localized shadows are one such factor. Night-survival operations could consist of thermal management, battery pre-charging, and load shedding. Some surface systems may hibernate through the night and then awake and continue nominal operations. Uncrewed mobile assets may use a more adaptive approach to optimize their power and operations; one method is to follow the sunlight. Night-survival operations may be initiated remotely by teleoperation, automated, or accomplished by supervised autonomous operation. The ability to pre-deploy and control remote assets in orbit or on Mars before the arrival of the mission crew is a key capability that can be simulated on the moon. The base camp provides a venue where these advanced operational concepts, technologies, and autonomous methods and techniques, including the incorporation of time delays to simulate Earth-Mars latency can be replicated to help buy down future Mars mission risks. This paper will examine the evolution of uncrewed lunar surface operations and support activities. It will also discuss the lunar surface environmental conditions (thermal, lighting, terrain, topography, communications) along with the challenges they pose on uncrewed surface operations, and the performance of these activities with limited to minimal human interaction and/or teleoperation. Since lunar missions include Mars mission analogs, such investigation provides the framework for future uncrewed Mars mission support.

Mark E Lewis

Effects of a Rotating Aerodynamic Probe on the Flow Field of a Compressor Rotor

An investigation of distortions of the rotor exit flow field caused by an aerodynamic probe mounted in the rotor is described in this paper. A rotor total pressure Kiel probe, mounted on the rotor hub and extending up to the mid-span radius of a rotor blade channel, generates a wake that forms additional flow blockage. Three types of high-response aerodynamic probes were used to investigate the distorted flow field behind the rotor. These probes were: a split-fiber thermo-anemometric probe to measure velocity and flow direction, a total pressure probe, and a disk probe for in-flow static pressure measurement. The signals acquired from these high-response probes were reduced using an ensemble averaging method based on a once per rotor revolution signal. The rotor ensemble averages were combined to construct contour plots for each rotor channel of the rotor tested. In order to quantify the rotor probe effects, the contour plots for each individual rotor blade passage were averaged into a single value. The distribution of these average values along the rotor circumference is a measure of changes in the rotor exit flow field due to the presence of a probe in the rotor. These distributions were generated for axial flow velocity and for static pressure.

Lepicovsky, Jan