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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

NASA Johnson Space Center Life Sciences Data System

The Life Sciences Project Division (LSPD) at JSC, which manages human life sciences flight experiments for the NASA Life Sciences Division, augmented its Life Sciences Data System (LSDS) in support of the Spacelab Life Sciences-2 (SLS-2) mission, October 1993. The LSDS is a portable ground system supporting Shuttle, Spacelab, and Mir based life sciences experiments. The LSDS supports acquisition, processing, display, and storage of real-time experiment telemetry in a workstation environment. The system may acquire digital or analog data, storing the data in experiment packet format. Data packets from any acquisition source are archived and meta-parameters are derived through the application of mathematical and logical operators. Parameters may be displayed in text and/or graphical form, or output to analog devices. Experiment data packets may be retransmitted through the network interface and database applications may be developed to support virtually any data packet format. The user interface provides menu- and icon-driven program control and the LSDS system can be integrated with other workstations to perform a variety of functions. The generic capabilities, adaptability, and ease of use make the LSDS a cost-effective solution to many experiment data processing requirements. The same system is used for experiment systems functional and integration tests, flight crew training sessions and mission simulations. In addition, the system has provided the infrastructure for the development of the JSC Life Sciences Data Archive System scheduled for completion in December 1994.

Rahman, Hasan↗
DOE OSTI2021

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗
NASA NTRS1984

Solar-terrestrial data access distribution and archiving

It is recommended that a central data catalog and data access network (CDC/DAN) for solar-terrestrial research be established, initially as a NASA pilot program. The system is envisioned to be flexible and to evolve as funds permit, starting from a catalog to an access network for high-resolution data. The report describes the various functional requirements for the CDC/DAN, but does not specify the hardware and software architectures as these are constantly evolving. The importance of a steering committee, working with the CDC/DAN organization, to provide scientific guidelines for the data catalog and for data storage, access, and distribution is also stressed.

Source record↗
DOE OSTI2023

Control of energy storage to reduce electric power system off-nominal frequency deviations

A hybrid power generation system is formed by the combination of an energy storage system (ESS) and a rotating synchronous power generator (SPG). Energy is stored in or released from the ESS in response to measurements of the at least one angle parameter, selected from rotor, torque, or power angle of the SPG, to provide active frequency damping of electrical power output. The control of ESS energy exchange increases the stabilizing impact of the SPG inertia on the frequency of electricity in an electrical network or power grid. The hybrid power generation system can have an effective equal area criterion for stability limit that is greater than that of the SPG operating without the ESS. The hybrid power generation system can enable the electrical network to have a greater proportion of variable or distributed energy resource (DER) power generation systems without otherwise exceeding stability limits.

Vartanian, Charles K.↗
DOE OSTI2024

Understanding electronic structure tunability by metal dopants for promoting MgB 2 hydrogenation

Hydrogen is a promising energy carrier, but its onboard application is limited by the need for compact, low-pressure storage solutions. Solid-state complex metal hydride systems, such as MgB 2 /Mg(BH 4 ) 2 , offer high storage capacities but suffer from sluggish kinetics and poor reversibility. One avenue for improving reactivity is to introduce metal dopants to alter electronic and atomic properties, but the role of these chemical additives remains poorly understood, particularly for the hydrogenation reaction. In this work, we used density functional theory calculations on model MgB 2 systems to rationalize the potential role of metal dopants in destabilizing B–B bonding within the MgB 2 lattice. We carried out detailed electronic structure analyses for 28 different metal dopant adatoms to identify properties that contribute to a dopant’s efficacy. Based on the simulation results, we propose that an intermediate ionic and covalent character of the bonds between adatoms and B atoms is desirable for facilitating charge redistribution, disrupting the B–B bond network, and promoting H 2 dissociation and H atom chemisorption on MgB 2 .

08 HYDROGEN↗
DOE OSTI2024

Zero-Power Analog Optical Processing

The motivation behind this research is the growing challenge of handling the massive amounts of data generated by modern imaging systems. Conventional digital image processing techniques are struggling to keep pace with the demands of high-resolution and high-speed imaging systems for remote sensing due to their high-power consumption and data storage requirements. We present a novel approach based on analog photonics to address this challenge. The proposed system utilizes a silicon-photonics-based image encoder positioned after image formation and initial optical-to-electrical conversion. The photonic encoder compresses image data using a passive disordered photonic structure to perform kernel-type random projections of the raw data. The compressed data is then processed by a back-end neural network, which reconstructs the original image with high fidelity (structural similarity exceeding 90%). Our proposed approach has the potential to compress images with ~ 1000X lower power consumption compared to digital approaches with data rates exceeding 1 terapixel/second.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

A neurocomputer based on an analog-digital hybrid architecture

A novel analog-digital hybrid architecture based on the utilization of high density digital random access memories for the storage of the synaptic weights of a neural network, and high speed analog hardware to perform neural computation is described. An electronic neurocomputer based on such an architecture is ideally suited for investigating the dynamics, associative recall properties, and computational capabilities of neural networks and provides significant speed improvement in comparison to conventional software based neural network simulations. As a demonstration of the feasibility of the hybrid architectural concept, a prototype breadboard hybrid neurocomputer system with 32 neurons has been designed and fabricated with off-the-shelf hardware components. The performance of the breadboard system has been tested for variety of applications including associative memory and combinatorial problem solving such as Graph Coloring, and is discussed in this paper.

Moopenn, A.↗
NASA NTRS2023

Development of Two High-Energy Bus ‘Cores’ for Rapid Support of Low-TRL and Educational Payloads: A Software-Configured EPS Combined with Flexible C&DH

For several years the TechEdSat flight series (TES-n), developed by the Nano Orbital Workshop (NOW) group at NASA Ames, has relied upon an in-house developed unit to serve both EPS (Electrical Power System) and C&DH (Command and Data Handling) roles along with low data-rate telemetry functions, i.e., serving as the ‘core’ of the spacecraft bus. This ‘core’ has a considerable task given the rapid cadence of the TES program and the typically low-TRL of payloads; configurability and compatibility are key to prevent mission-specific hardware. However, at only 15 watts the current core has become insufficient to support the program’s growing missions and increasingly demanding payloads. To this end, the NOW program is developing new cores to support two TES mission classes: a single-PCB ‘MiniCore’ designed to support 80-watt missions 6U or smaller in LEO, and a three-PCB, radiation-tolerant ‘StackCore’ designed to support 6U and larger missions over 500 watts in LEO and beyond. The ‘MiniCore’ design consists of three main segments: a processor-agnostic C&DH, a software-configured EPS, and a backup low data-rate radio. The design philosophy was to enable rapid-manufacture in a turbulent supply chain, hence the design consists of COTS parts with a focus on those able to be drop-in replaced with radiation-tolerant versions when demanded by the mission. As a single PC-104 sized circuit board, power density and ease of integration also dominated design, demanding the use of modern features such as single-point USB-C for easy charging and monitoring of the spacecraft on the ground. The ‘MiniCore’ can support 80 watts of load, 140 watt-hours of storage, and over 20 watts of optimized solar generation with extensive power monitoring throughout. The ‘MiniCore’ supports one battery pack, six solar-panels, six loads, five actuators, Iridium SBD, and an internal 802.15.4 network. Additionally, the processor-agnostic design can accept any PJRC Teensy 3.x or Adafruit Feather microcontroller unit to enable processor scaling with mission requirements or environment. It is expected a development unit of this design will be completed before conference. The ‘StackCore’ design consists of three stacked PC-104 sized circuit boards: one dedicated to power generation and storage, one dedicated to power distribution, and one dedicated to C&DH tasks. This delineation is necessary to support the transition from highly integrated ICs to discrete analog circuitry, enabling a primarily analog control power system able to operate without software in a radiation environment with finer monitoring compared to the ‘MiniCore’ design. The planned base architecture supports over 500 watts of load, 250 watt-hours of storage, and over 80 watts of optimized solar generation. The power distribution board allows for the use of daughter cards hosting custom converters or interfaces for payloads, in addition to the software-configured supplies used on the ‘MiniCore’. This core stack will be managed by a Vorago ARM M4 microcontroller and support the same wireless communications as the ‘MiniCore’, with optional integration of a NOW S-band radio and attitude determination sensors for ‘black box’ functionality. It is expected the prototype will still be in development during conference.

Spacecraft↗
NASA NTRSDate not supplied

Development of Two High-Energy Bus ‘Cores’ for Rapid Support of Low-TRL and Educational Payloads: A Software-Configured EPS Combined with Flexible C&DH

For several years the TechEdSat flight series (TES-n), developed by the Nano Orbital Workshop (NOW) group at NASA Ames, has relied upon an in-house developed unit to serve both EPS (Electrical Power System) and C&DH (Command and Data Handling) roles along with low data-rate telemetry functions, i.e., serving as the ‘core’ of the spacecraft bus. This ‘core’ has a considerable task given the rapid cadence of the TES program and the typically low-TRL of payloads; configurability and compatibility are key to prevent mission-specific hardware. However, at only 15 watts the current core has become insufficient to support the program’s growing missions and increasingly demanding payloads. To this end, the NOW program is developing new cores to support two TES mission classes: a single-PCB ‘MiniCore’ designed to support 80-watt missions 6U or smaller in LEO, and a three-PCB, radiation-tolerant ‘StackCore’ designed to support 6U and larger missions over 500 watts in LEO and beyond. The ‘MiniCore’ design consists of three main segments: a processor-agnostic C&DH, a software-configured EPS, and a backup low data-rate radio. The design philosophy was to enable rapid-manufacture in a turbulent supply chain, hence the design consists of COTS parts with a focus on those able to be drop-in replaced with radiation-tolerant versions when demanded by the mission. As a single PC-104 sized circuit board, power density and ease of integration also dominated design, demanding the use of modern features such as single-point USB-C for easy charging and monitoring of the spacecraft on the ground. The ‘MiniCore’ can support 80 watts of load, 140 watt-hours of storage, and over 20 watts of optimized solar generation with extensive power monitoring throughout. The ‘MiniCore’ supports one battery pack, six solar-panels, six loads, five actuators, Iridium SBD, and an internal 802.15.4 network. Additionally, the processor-agnostic design can accept any PJRC Teensy 3.x or Adafruit Feather microcontroller unit to enable processor scaling with mission requirements or environment. It is expected a development unit of this design will be completed before conference. The ‘StackCore’ design consists of three stacked PC-104 sized circuit boards: one dedicated to power generation and storage, one dedicated to power distribution, and one dedicated to C&DH tasks. This delineation is necessary to support the transition from highly integrated ICs to discrete analog circuitry, enabling a primarily analog control power system able to operate without software in a radiation environment with finer monitoring compared to the ‘MiniCore’ design. The planned base architecture supports over 500 watts of load, 250 watt-hours of storage, and over 80 watts of optimized solar generation. The power distribution board allows for the use of daughter cards hosting custom converters or interfaces for payloads, in addition to the software-configured supplies used on the ‘MiniCore’. This core stack will be managed by a Vorago ARM M4 microcontroller and support the same wireless communications as the ‘MiniCore’, with optional integration of a NOW S-band radio and attitude determination sensors for ‘black box’ functionality. It is expected the prototype will still be in development during conference.

Spacecraft↗
NASA NTRSDate not supplied

Development of Two High-Energy Bus ‘Cores’

For several years the TechEdSat flight series (TES-n), developed by the Nano Orbital Workshop (NOW) group at NASA Ames, has relied upon an in-house developed unit to serve both EPS (Electrical Power System) and C&DH (Command and Data Handling) roles along with low data-rate telemetry functions, i.e., serving as the ‘core’ of the spacecraft bus. This ‘core’ has a considerable task given the rapid cadence of the TES program and the typically low-TRL of payloads; configurability and compatibility are key to prevent mission-specific hardware. However, at only 15 watts the current core has become insufficient to support the program’s growing missions and increasingly demanding payloads. To this end, the NOW program is developing new cores to support two TES mission classes: a single-PCB ‘MiniCore’ designed to support 80-watt missions 6U or smaller in LEO, and a three-PCB, radiation-tolerant ‘StackCore’ designed to support 6U and larger missions over 500 watts in LEO and beyond. The ‘MiniCore’ design consists of three main segments: a processor-agnostic C&DH, a software-configured EPS, and a backup low data-rate radio. The design philosophy was to enable rapid-manufacture in a turbulent supply chain, hence the design consists of COTS parts with a focus on those able to be drop-in replaced with radiation-tolerant versions when demanded by the mission. As a single PC-104 sized circuit board, power density and ease of integration also dominated design, demanding the use of modern features such as single-point USB-C for easy charging and monitoring of the spacecraft on the ground. The ‘MiniCore’ can support 80 watts of load, 140 watt-hours of storage, and over 20 watts of optimized solar generation with extensive power monitoring throughout. The ‘MiniCore’ supports one battery pack, six solar-panels, six loads, five actuators, Iridium SBD, and an internal 802.15.4 network. Additionally, the processor-agnostic design can accept any PJRC Teensy 3.x or Adafruit Feather microcontroller unit to enable processor scaling with mission requirements or environment. It is expected a development unit of this design will be completed before conference. The ‘StackCore’ design consists of three stacked PC-104 sized circuit boards: one dedicated to power generation and storage, one dedicated to power distribution, and one dedicated to C&DH tasks. This delineation is necessary to support the transition from highly integrated ICs to discrete analog circuitry, enabling a primarily analog control power system able to operate without software in a radiation environment with finer monitoring compared to the ‘MiniCore’ design. The planned base architecture supports over 500 watts of load, 250 watt-hours of storage, and over 80 watts of optimized solar generation. The power distribution board allows for the use of daughter cards hosting custom converters or interfaces for payloads, in addition to the software-configured supplies used on the ‘MiniCore’. This core stack will be managed by a Vorago ARM M4 microcontroller and support the same wireless communications as the ‘MiniCore’, with optional integration of a NOW S-band radio and attitude determination sensors for ‘black box’ functionality. It is expected the prototype will still be in development during conference.

Avery Brock↗
DOE OSTI2021

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗
DOE OSTI2026

Launch Alaska Transportation and Energy Accelerator (LATEA)

The Launch Alaska Transportation and Energy Accelerator (LATEA), funded through the U.S. Department of Energy Office of Technology Commercialization’s Energy Program for Innovation Clusters (EPIC),advanced deployment of innovative and efficient transportation and energy technology in Alaska from October 2021 through June 2025. The project was designed to leverage Launch Alaska’s accelerator model to identify, recruit, and support transportation technology companies with novel solutions to market needs while building the stakeholder networks, demonstration opportunities, and institutional capacity necessary to accelerate commercialization in one of the most challenging operating environments in the United States.

08 HYDROGEN↗
DOE OSTI2025

dCache: The Storage System of Choice for Data-Intensive Applications

The ever-increasing volumes of data produced by modern scientific facilities like EuXFEL and LHC put significant stress on data management infrastructure operated by laboratories and research centers. The challenges to be addressed span the entire data life cycle, from ingest and efficient data analysis to long-term preservation, typically involving large tape libraries. dCache, a storage system developed in collaboration between the Deutsches Elektronen-Synchrotron (DESY), Fermi National Accelerator Laboratory, and Nordic e-Infrastructure Collaboration (NeIC), is designed to manage a large number of disk servers and to facilitate transparent data migration to and from archival storage. Its multifaceted approach offers a unified method to support a variety of scientific use cases with the same storage infrastructure, including high-throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters, and long-term data preservation on tertiary storage. Initially developed for high energy physics (HEP) experiments, dCache is now used by various scientific communities, including astrophysics, biomedical research, and life sciences, each having specific requirements. This paper presents architecture, deployment strategies, performance and scalability enhancements, and recent advancements in dCache addressing the needs of scientific communities. Finally, we touch on the development and release process, ensuring the software’s high quality.

DCache↗
DOE OSTI2024

Extending Rucio with modern cloud storage support

Rucio is a software framework designed to facilitate scientific collaborations in efficiently organising, managing, and accessing extensive volumes of data through customizable policies. The framework enables data distribution across globally distributed locations and heterogeneous data centres, integrating various storage and network technologies into a unified federated entity. Rucio offers advanced features like distributed data recovery and adaptive replication, and it exhibits high scalability, modularity, and extensibility. Originally developed to meet the requirements of the high-energy physics experiment ATLAS, Rucio has been continuously expanded to support LHC experiments and diverse scientific communities. Recent R&D projects within these communities have evaluated the integration of both private and commercially-provided cloud storage systems, leading to the development of additional functionalities for seamless integration within Rucio. Furthermore, the underlying systems, FTS and GFAL/Davix, have been extended to cater to specific use cases. This contribution focuses on the technical aspects of this work, particularly the challenges encountered in building a generic interface for self-hosted cloud storage, such as MinIO or CEPH S3 Gateway, and established providers like Google Cloud Storage and Amazon Simple Storage Service. Additionally, the integration of decentralised clouds like SEAL is explored. Key aspects, including authentication and authorisation, direct and remote access, throughput and cost estimation, are highlighted, along with shared experiences in daily operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Coordination of Energy Storage and Distributed Generation for Voltage Control and Peak-valley Filling

The increasing penetration of distributed energy resources (DERs) in distribution network (DN) poses challenges on voltage control. In addition, the growing integration of DERs also reshapes the traditional load profile. To comprehensively address the voltage control and peak-valley filling in DN, this paper proposes a model predictive control (MPC) based optimization framework. The proposed method can achieve coordinated voltage control and peak-valley filling by adjusting the reactive power output from distributed generations (DGs) and the charging/discharging of energy storage systems (ESS). The performance of the proposed method is demonstrated by simulations on a modified IEEE-123 bus system.

Zhang, Zhengfa [University of Tennessee, Knoxville↗
DOE OSTI2019

Energy storage: The future enabled by nanomaterials

Lithium-ion batteries, which power portable electronics, electric vehicles, and stationary storage, have been recognized with the 2019 Nobel Prize in chemistry. The development of nanomaterials and their related processing into electrodes and devices can improve the performance and/or development of the existing energy storage systems. We provide a perspective on recent progress in the application of nanomaterials in energy storage devices, such as supercapacitors and batteries. The versatility of nanomaterials can lead to power sources for portable, flexible, foldable, and distributable electronics; electric transportation; and grid-scale storage, as well as integration in living environments and biomedical systems. To overcome limitations of nanomaterials related to high reactivity and chemical instability caused by their high surface area, nanoparticles with different functionalities should be combined in smart architectures on nano- and microscales. The integration of nanomaterials into functional architectures and devices requires the development of advanced manufacturing approaches. We discuss successful strategies and outline a roadmap for the exploitation of nanomaterials for enabling future energy storage applications, such as powering distributed sensor networks and flexible and wearable electronics.

catalysis (heterogeneous)↗
NASA NTRS2005

New Directions in Space Operations Services in Support of Interplanetary Exploration

To gain access to the necessary operational processes and data in support of NASA's Lunar/Mars Exploration Initiative, new services, adequate levels of computing cycles and access to myriad forms of data must be provided to onboard spacecraft and ground based personnel/systems (earth, lunar and Martian) to enable interplanetary exploration by humans. These systems, cycles and access to vast amounts of development, test and operational data will be required to provide a new level of services not currently available to existing spacecraft, on board crews and other operational personnel. Although current voice, video and data systems in support of current space based operations has been adequate, new highly reliable and autonomous processes and services will be necessary for future space exploration activities. These services will range from the more mundane voice in LEO to voice in interplanetary travel which because of the high latencies will require new voice processes and standards. New services, like component failure predictions based on data mining of significant quantities of data, located at disparate locations, will be required. 3D or holographic representation of onboard components, systems or family members will greatly improve maintenance, operations and service restoration not to mention crew morale. Current operational systems and standards, like the Internet Protocol, will not able to provide the level of service required end to end from an end point on the Martian surface like a scientific instrument to a researcher at a university. Ground operations whether earth, lunar or Martian and in flight operations to the moon and especially to Mars will require significant autonomy that will require access to highly reliable processing capabilities, data storage based on network storage technologies. Significant processing cycles will be needed onboard but could be borrowed from other locations either ground based or onboard other spacecraft. Reliability will be a key factor with onboard and distributed backup processing an absolutely necessary requirement. Current cluster processing/Grid technologies may provide the basis for providing these services. An overview of existing services, future services that will be required and the technologies and standards required to be developed will be presented. The purpose of this paper will be to initiate a technological roadmap, albeit at a high level, of current voice, video, data and network technologies and standards (which show promise for adaptation or evolution) to what technologies and standards need to be redefined, adjusted or areas where new ones require development. The roadmap should begin the differentiation between non manned and manned processes/services where applicable. The paper will be based in part on the activities of the CCSDS Monitor and Control working group which is beginning the process of standardization of the these processes. Another element of the paper will be based on an analysis of current technologies supporting space flight processes and services at JSC, MSFC, GSFC and to a lesser extent at KSC. Work being accomplished in areas such as Grid computing, data mining and network storage at ARC, IBM and the University of Alabama at Huntsville will be researched and analyzed.

Bradford, Robert N.↗
DOE OSTI2025

A Convolution Neural Network for Voltage Event Classification at a Photovoltaic Inverter

This paper presents a convolutional neural network (CNN) developed to identify voltage events in photovoltaic (PV) inverters. The CNN is trained on synthetic data generated using the IEEE 13-bus distribution feeder model and evaluated on field measured data collected from Energy Northwest’s Horn Rapids Solar, Storage, and Training (HRSST) facility. The study focuses on two common voltage events: faults and voltage sags. The CNN is configured to analyze voltage and current waveforms from three-phase PV systems, demonstrating excellent accuracy during training. Field data from the HRSST facility is employed to assess its real-world performance, where the CNN achieves perfect identification of faults and voltage sags in a sample of nine events. This work highlights the potential of the proposed method to enhance PV protection schemes, providing a robust foundation for improved voltage event detection and grid reliability.

Cornachione, Matthew A.↗