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Development and Validation of a High-Vacuum Thermal Conductivity Testbed for Aerospace Interface Materials

Thermal Interface Materials (TIMs) are critical components in spacecraft thermal management systems, where thermal performance is strongly influenced by vacuum conditions, interface contact resistance, and layered metallic joint behavior. However, manufacturer-reported thermal conductivity values are often derived under idealized conditions and may not accurately represent performance within operational aerospace applications. To address this limitation, the Testbed for Advanced Interface Materials in Vacuum (TAIMV) was developed as a modular vacuum-compatible thermal conductivity characterization platform capable of evaluating aerospace-relevant TIM configurations under both ambient and high-vacuum environments. The testbed was derived from the ASTM C1044-16 guarded hot plate methodology and incorporates interchangeable layers of stainless steel coupon geometries, independently controlled main and guard heaters, embedded resistance temperature detectors (RTDs), thermocouples, multi-layer insulation (MLI), and a temperature-controlled cold plate to characterize through-thickness thermal gradients across layered interfaces. In the current configuration, interface compression is limited to the nominal contact pressure generated by the experimental stack assembly. Initial experimental campaigns were conducted at ambient pressure and below 1×10-5 torr for vacuum cases using multiple interface materials including Braycote 601EF and Krytox-based greases across a range of thermal operating conditions. In parallel, a coupled numerical Python thermal model was developed to predict temperature distribution throughout the stack while accounting for conduction, radiation, and parasitic heat transfer pathways and effective interface resistance effects. Experimental measurements and numerical predictions showed consistent thermal trends across multiple operating conditions and environmental states. Results also revealed measurable differences between ambient and vacuum thermal behavior, demonstrating the importance of interface resistance, parasitic heat transfer mechanisms, and stack geometry in determining effective thermal performance within layered thermal interfaces. The presented work establishes a foundation for future thermal model correlation efforts and expanded characterization of aerospace thermal interface materials under representative environmental conditions. Future work will focus on the integration of a load cell system to enable controlled pressure-dependent characterization of thermal interface materials under compressive loading. This capability will allow investigation of the influence of contact pressure on effective thermal conductivity, interface resistance, and thermal performance within layered aerospace thermal interfaces under representative operational conditions.

Thermal Development Testing↗

Data Center Cybersecurity, Supply Chain Risk Management, and Emerging Regulation Cohort Summary: Takeaways and Action Plans

This report summarizes the outcomes of the Data Center Cohort under the Department of Energy’s Technical Assistance for Digital Assurance (TADA) initiative, aimed at enhancing grid resilience through cybersecurity, supply chain risk management (SCRM), and Cyber-Informed Engineering (CIE). The cohort engaged 17 organizations across utilities, data center operators, vendors, and technology providers in three sessions combining presentations, discussions, and exercises. Key topics included AI-driven load behavior, cybersecurity vulnerabilities in UPS/BESS and cooling systems, governance gaps at utility–data center boundaries, and supply chain integrity. Five cross-cutting themes emerged: interconnection architecture vulnerabilities, fragmented governance, AI-driven stability risks, lack of regulatory frameworks, and long-term supply chain concerns. Actionable recommendations were developed, including implementing DMZ segmentation, formalizing vendor access agreements, designing AI workload limits, and advancing standards through NERC and state-level programs. These strategies aim to strengthen resilience, clarify responsibilities, and ensure secure integration of data centers into the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗

Deep Reinforcement Learning for Resilient Power and Energy Systems: Progress, Prospects, and Future Avenues

In recent years, deep reinforcement learning (DRL) has garnered substantial attention in the context of enhancing resilience in power and energy systems. Resilience, characterized by the ability to withstand, absorb, and quickly recover from natural disasters and human-induced disruptions, has become paramount in ensuring the stability and dependability of critical infrastructure. This comprehensive review delves into the latest advancements and applications of DRL in enhancing the resilience of power and energy systems, highlighting significant contributions and key insights. The exploration commences with a concise elucidation of the fundamental principles of DRL, highlighting the intricate interplay among reinforcement learning (RL), deep learning, and the emergence of DRL. Furthermore, it categorizes and describes various DRL algorithms, laying a robust foundation for comprehending the applicability of DRL. The linkage between DRL and power system resilience is forged through a systematic classification of DRL applications into five pivotal dimensions: dynamic response, recovery and restoration, energy management and control, communications and cybersecurity, and resilience planning and metrics development. This structured categorization facilitates a methodical exploration of how DRL methodologies can effectively tackle critical challenges within the domain of power and energy system resilience. The review meticulously examines the inherent challenges and limitations entailed in integrating DRL into power and energy system resilience, shedding light on practical challenges and potential pitfalls. Additionally, it offers insights into promising avenues for future research, with the aim of inspiring innovative solutions and further progress in this vital domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Real-Time Lifetime Prediction of Semiconductor Devices Using Hardware-in-the-Loop

This paper presents a unique approach to enable real-time lifespan prediction of semiconductor power modules using a Hardware-in-the-Loop (HIL) system. By integrating the module's overall loss characteristics-specifically switching and conduction losses-with a thermoelectric model of the thermal management system, this research demonstrates that the model can dynamically estimates the junction temperature profile of the semiconductor devices in response to a changing torque demand profile for the motor drive system. This capability enables continuous monitoring of the module's operational time and cumulative stress induced on the devices to compute accumulated remaining lifetime or time-to-failure (TTF). This study provides an architectural framework for the HIL system with high-fidelity component models of multiple physical domains, allowing simulation of dynamic behaviors of a closely-coupled motor drive system. The advanced real-time computation and measurement functionalities of the HIL system allow for both dynamic lifetime calculations based on simulated data and aggregate lifetime predictions utilizing historical data. Moreover, this paper details an algorithm that not only computes cumulative damage but also synthesizes these data into a comprehensive aggregated lifetime metric. This methodology can enhance the maintenance scheduling strategies and operational reliability of semiconductor devices in critical applications, ultimately extending their service life while optimizing performance.

hardware-in-the-loop (HIL)↗

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗

Total Quality Management: Analysis, Evaluation and Implementation Within ACRV Project Teams

Total quality management (TQM) is a cooperative form of doing business that relies on the talents of everyone in an organization to continually improve quality and productivity, using teams and an assortment of statistical and measurement tools. The Assured Crew Return Vehicle (ACRV) Project Office was identified as an excellent project in which to demonstrate the applications and benefits of TQM processes. As the ACRV Program moves through its various stages of development, it is vital that effectiveness and efficiency be maintained in order to provide the Space Station Freedom (SSF) crew an affordable, on-time assured return to Earth. A critical factor for the success of the ACRV is attaining the maximum benefit from the resources applied to the program. Through a series of four tutorials on various quality improvement techniques, and numerous one-on-one sessions during the SSF's 10-week term in the project office, results were obtained which are aiding the ACRV Office in implementing a disciplined, ongoing process for generating fundamental decisions and actions that shape and guide the organization. Significant advances were made in improving the processes for two particular groups - the correspondence distribution team and the WATER Test team. Numerous people from across JSC were a part of the various team activities including engineering, man systems, and safety. The work also included significant interaction with the support contractor to the ACRV Project. The results of the improvement activities can be used as models for other organizations desiring to operate under a system of continuous improvement. In particular, they have advanced the ACRV Project Teams further down the path of continuous improvement, in support of a working philosophy of TQM.

Raiman, Laura B.↗

Management of Guidance, Navigation, and Control Technologies for Spacecraft Formations Under the NASA Cross Enterprise Technology Development Program (CETDP)

Breakthrough technology development is critical to securing the future of our space industry. The National Aeronautics and Space Administration (NASA) Cross-Enterprise Technology Development Program (CETDP) is developing critical space technologies that enable innovative and less costly missions, and spawn new mission opportunities through revolutionary, long-term, high-risk, high-payoff technology advances. The CETDP is a NASA-wide activity managed by the Advanced Technology and Mission Studies Division (AT&MS) at Headquarters Office of Space Science. Program management for CETDP is distributed across the multiple NASA Centers and draws on expertise throughout the Agency. The technology research activities are organized along Project-level divisions called thrust areas that are directly linked to the Agency's goals and objectives of the Enterprises: Earth Science, Space Science, Human Exploration and Development of Space; and the Office of the Chief Technologist's (OCT) strategic technology areas. Cross-Enterprise technology is defined as long-range strategic technologies that have broad potential to span the needs of more than one Enterprise. Technology needs are identified and prioritized by each of the primary customers. The thrust area manager (TAM) for each division is responsible for the ultimate success of technologies within their area, and can draw from industry, academia, other government agencies, other CETDP thrust areas, and other NASA Centers to accomplish the goals of the thrust area. An overview of the CETDP and description of the future directions of the thrust area called Distributed Spacecraft are presented in this paper. Revolutionary technologies developed within this thrust area will enable the implementation of a spatially distributed network of individual vehicles, or assets, collaborating as a single collective unit, and exhibiting a common system-wide capability to accomplish a shared objective. With such a capability, new Earth and space science measurement concepts become a reality.

Hartman, Kathy↗

Management of Guidance, Navigation and Control Technologies for Spacecraft Formations under the NASA Cross-Enterprise Technology Development Program (CETDP)

Breakthrough technology development is critical to securing the future of our space industry. The National Aeronautics and Space Administration (NASA) Cross-Enterprise Technology Development Program (CETDP) is developing critical space technologies that enable innovative and less costly missions, and spawn new mission opportunities through revolutionary, long-term, high-risk, high-payoff technology advances. The CETDP is a NASA-wide activity managed by the Advanced Technology and Mission Studies Division (AT&MS) at Headquarters Office of Space Science. Program management for CETDP is distributed across the multiple NASA Centers and draws on expertise throughout the Agency. The technology research activities are organized along Project-level divisions called thrust areas that are directly linked to the Agency's goals and objectives of the Enterprises: Earth Science, Space Science, Human Exploration and Development of Space; and the Office of the Chief Technologist's (OCT) strategic technology areas. Cross-Enterprise technology is defined as long-range strategic technologies that have broad potential to span the needs of more than one Enterprise. Technology needs are identified and prioritized by each of the primary customers. The thrust area manager (TAM) for each division is responsible for the ultimate success of technologies within their area, and can draw from industry, academia, other government agencies, other CETDP thrust areas, and other NASA Centers to accomplish the goals of the thrust area. An overview of the CETDP and description of the future directions of the thrust area called Distributed Spacecraft are presented in this paper. Revolutionary technologies developed within this thrust area will enable the implementation of a spatially distributed network of individual vehicles, or assets, collaborating as a single collective unit, and exhibiting a common system-wide capability to accomplish a shared objective. With such a capability, new Earth and space science measurement concepts become a reality.

Hartman, Kathy↗

Reactive Sequencing for Autonomous Navigation Evolving from Phoenix Entry, Descent, and Landing

Virtual Machine Language (VML) is an award-winning advanced procedural sequencing language in use on NASA deep-space missions since 1997, and was used for the successful entry, descent, and landing (EDL) of the Phoenix spacecraft onto the surface of Mars. Phoenix EDL utilized a state-oriented operations architecture which executed within the constraints of the existing VML 2.0 flight capability, compatible with the linear "land or die" nature of the mission. The intricacies of Phoenix EDL included the planned discarding of portions of the vehicle, the complex communications management for relay through on-orbit assets, the presence of temporally indeterminate physical events, and the need to rapidly catch up four days of sequencing should a reboot of the spacecraft flight computer occur shortly before atmospheric entry. These formidable operational challenges led to new techniques for packaging and coordinating reusable sequences called blocks using one-way synchronization via VML sequencing global variable events. The coordinated blocks acted as an ensemble to land the spacecraft, while individually managing various elements in as simple a fashion as possible. This paper outlines prototype VML 2.1 flight capabilities that have evolved from the one-way synchronization techniques in order to implement even more ambitious autonomous mission capabilities. Target missions for these new capabilities include autonomous touch-and-go sampling of cometary and asteroidal bodies, lunar landing of robotic missions, and ultimately landing of crewed lunar vehicles. Close proximity guidance, navigation, and control operations, on-orbit rendezvous, and descent and landing events featured in these missions require elaborate abort capability, manifesting highly non-linear scenarios that are so complex as to overtax traditional sequencing, or even the sort of one-way coordinated sequencing used during EDL. Foreseeing advanced command and control needs for small body and lunar landing guidance, navigation and control scenarios, work began three years ago on substantial upgrades to VML that are now being exercised in scenarios for lunar landing and comet/asteroid rendezvous. The advanced state-based approach includes coordinated state transition machines with distributed decision-making logic. These state machines are not merely sequences - they are reactive logic constructs capable of autonomous decision making within a well-defined domain. Combined with the JPL's AutoNav software used on Deep Space 1 and Deep Impact, the system allows spacecraft to autonomously navigate to an unmapped surface, soft-contact, and either land or ascend. The state machine architecture enabled by VML 2.1 has successfully performed sampling missions and lunar descent missions in a simulated environment, and is progressing toward flight capability. The authors are also investigating using the VML 2.1 flight director architecture to perform autonomous activities like rendezvous with a passive hypothetical Mars sample return capsule. The approach being pursued is similar to the touch-and-go sampling state machines, with the added complications associated with the search for, physical capture of, and securing of a separate spacecraft. Complications include optically finding and tracking the Orbiting Sample Capsule (OSC), keeping the OSC illuminated, making orbital adjustments, and physically capturing the OSC. Other applications could include autonomous science collection and fault compensation.

asteroid↗

Computational Model of Human and System Dynamics in Free Flight: Studies in Distributed Control Technologies

This paper presents a set of studies in full mission simulation and the development of a predictive computational model of human performance in control of complex airspace operations. NASA and the FAA have initiated programs of research and development to provide flight crew, airline operations and air traffic managers with automation aids to increase capacity in en route and terminal area to support the goals of safe, flexible, predictable and efficient operations. In support of these developments, we present a computational model to aid design that includes representation of multiple cognitive agents (both human operators and intelligent aiding systems). The demands of air traffic management require representation of many intelligent agents sharing world-models, coordinating action/intention, and scheduling goals and actions in a potentially unpredictable world of operations. The operator-model structure includes attention functions, action priority, and situation assessment. The cognitive model has been expanded to include working memory operations including retrieval from long-term store, and interference. The operator's activity structures have been developed to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. System stability and operator actions can be predicted by using the model. The model's predictive accuracy was verified using the full-mission simulation data of commercial flight deck operations with advanced air traffic management techniques.

Corker, Kevin M.↗

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Monolithic Microwave Integrated Circuit (MMIC) Phased Array Demonstrated With ACTS

Monolithic Microwave Integrated Circuit (MMIC) arrays developed by the NASA Lewis Research Center and the Air Force Rome Laboratory were demonstrated in aeronautical terminals and in mobile or fixed Earth terminals linked with NASA's Advanced Communications Technology Satellite (ACTS). Four K/Ka-band experimental arrays were demonstrated between May 1994 and May 1995. Each array had GaAs MMIC devices at each radiating element for electronic beam steering and distributed power amplification. The 30-GHz transmit array used in uplinks to ACTS was developed by Lewis and Texas Instruments. The three 20-GHz receive arrays used in downlinks from ACTS were developed in cooperation with the Air Force Rome Laboratory, taking advantage of existing Air Force integrated-circuit, active-phased-array development contracts with the Boeing Company and Lockheed Martin Corporation. Four demonstrations, each related to an application of high interest to both commercial and Department of Defense organizations, were conducted. The location, type of link, and the data rate achieved for each of the applications is shown. In one demonstration-- an aeronautical terminal experiment called AERO-X--a duplex voice link between an aeronautical terminal on the Lewis Learjet and ACTS was achieved. Two others demonstrated duplex voice links (and in one case, interactive video links as well) between ACTS and an Army high-mobility, multipurpose wheeled vehicle (HMMWV, or "humvee"). In the fourth demonstration, the array was on a fixed mount and was electronically steered toward ACTS. Lewis served as project manager for all demonstrations and as overall system integrator. Lewis engineers developed the array system including a controller for open-loop tracking of ACTS during flight and HMMWV motion, as well as a laptop data display and recording system used in all demonstrations. The Jet Propulsion Laboratory supported the AERO-X program, providing elements of the ACTS Mobile Terminal. The successful performance of experimental, proof-of-concept MMIC K/Ka-band arrays developed with U.S. industry in field demonstrations with ACTS indicates that high density MMIC integration at 20 and 30 GHz is indeed feasible. The successful development and demonstration of the MMIC array systems was possible only because of significant intergovernmental and Government/industry cooperation and the high level of teamwork within Lewis. The results provide a strong incentive for continuing the focused development of MMIC-array technology for satellite communications applications, with emphasis on packaging and cost issues, and for continuing the planning and conducting of other appropriate demonstrations or experiments of phased-array technology with ACTS. Given the present pressures on reducing funding for research and development in Government and industry, the extent to which this can be continued in a cooperative manner will determine whether MMIC array technology will make the transition from the proof-of-concept level to the operational system level.

Source record↗

Advanced Solar and Load Forecasting Incorporating HD Sky Imaging: BNL Phase II Activities (Final Report)

Over the last ten years, lower costs and government incentives for rooftop and utility scale solar photovoltaic (PV) systems have led to a rapid growth in the amount of power generated from this renewable energy source. For example, the cumulative PV generating capacity of 1,160 MW in New York State at the end of 2018 represents a growth of more than 4,000% over the past seven years and almost 400% over the past five years. But increased dependence on this inherently variable energy source introduces the need to anticipate, i.e., forecast, changes in energy production and manage them appropriately. Utilities and grid operators can then use this forecast information to balance changes and maintain stability of the electric grid by adding additional sources or diverting excess supplies for sale or storage, as needed. Current techniques based on persistence modeling are not accurate enough to provide reliable forecasts. With support from the U.S. Department of Energy’s Solar Energy Technology Office (DOE SETO) and the New York Power Authority (NYPA), Brookhaven National Laboratory (BNL), the National Center for Atmospheric Research (NCAR), and the Electric Power Research Institute (EPRI) formed a collaborative team to provide reliable forecasting over a range of time intervals. In addition, the forecasting area was scaled up to about 50 km2, a factor of 20 times larger than previously achieved, so that available solar irradiance could be forecast throughout an entire region including both large generating facilities and distributed rooftop solar arrays. In its role, BNL developed a technology for predicting changes in available solar energy from zero to 30 minutes ahead. This “nowcasting” approach uses inexpensive, off-the-shelf, high definition (HD) imagers with custom software to identify and track the movement of approaching clouds and predict their impact on available solar irradiance. The BNL Nowcasting model improves forecasting accuracy by 20 to 50% over current techniques. Forecasting reliability for low clouds (worst case scenario since they move over solar panels more rapidly than high clouds) was calculated to be 95% accurate for forecast periods of five minute ahead. Reliability decreases with longer forecast time intervals and was calculated to be about 80% for 10 minute forecasts, and about 70% for 20 minutes ahead. Clouds were still reliably tracked by the imager network at 60% accuracy for forecast lead times up to about 30 minutes ahead, and this was determined to be the practical nowcasting limit for low clouds in a network of this scale. This work represents the second phase of a multi-phase effort to develop and deploy solar forecasting at a regional scale so that contributions from distributed rooftop solar resources can be forecast along with solar generating facilities, giving utilities and stakeholders an accurate assessment of future energy production. Additional work is planned to operate the forecasting network in an area upstate New York to assess system reliability under diverse meteorological conditions and to monitor system performance over a full range of seasonal variability.

14 SOLAR ENERGY↗

Electric Power System Technology Options for Lunar Surface Missions

In 2004, the President announced a 'Vision for Space Exploration' that is bold and forward-thinking, yet practical and responsible. The vision explores answers to longstanding questions of importance to science and society and will develop revolutionary technologies and capabilities for the future, while maintaining good stewardship of taxpayer dollars. One crucial technology area enabling all space exploration is electric power systems. In this paper, the author evaluates surface power technology options in order to identify leading candidate technologies that will accomplish lunar design reference mission three (LDRM-3). LDRM-3 mission consists of multiple, 90-day missions to the lunar South Pole with 4-person crews starting in the year 2020. Top-level power requirements included a nominal 50 kW continuous habitat power over a 5-year lifetime with back-up or redundant emergency power provisions and a nominal 2-kW, 2-person unpressurized rover. To help direct NASA's technology investment strategy, this lunar surface power technology evaluation assessed many figures of merit including: current technology readiness levels (TRLs), potential to advance to TRL 6 by 2014, effectiveness of the technology to meet the mission requirements in the specified time, mass, stowed volume, deployed area, complexity, required special ground facilities, safety, reliability/redundancy, strength of industrial base, applicability to other LDRM-3 elements, extensibility to Mars missions, costs, and risks. For the 50-kW habitat module, dozens of nuclear, radioisotope and solar power technologies were down-selected to a nuclear fission heat source with Brayton, Stirling or thermoelectric power conversion options. Preferred energy storage technologies included lithium-ion battery and Proton Exchange Membrane (PEM) Regenerative Fuel Cells (RFC). Several AC and DC power management and distribution architectures and component technologies were defined consistent with the preferred habitat power generation technology option and the overall lunar surface mission. For rover power, more than 20 technology options were down-selected to radioisotope Stirling, liquid lithium-ion battery, PEM RFC, or primary fuel cell options. The author discusses various conclusions that can be drawn from the findings of this surface power technologies evaluation.

Kerslake, Thomas W.↗

VTK-m User's' Guide (V.1.7)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.This book includes contributions from the VTK-m community including the VTK-m development team and the user community.

97 MATHEMATICS AND COMPUTING↗

The VTK-m Users' Guide (V.1.9)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗