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At least 1,153 records · Page 64

The NASA telerobot technology demonstrator

The ongoing development of a telerobot technology demonstrator is reported. The demonstrator is implemented as a laboratory-based research testbed, and will show proof-of-concept for supervised automation of space assembly, servicing, and repair operations. The demonstrator system features a hierarchically layered intelligent control architecture which enables automated planning and run-time sequencing of complex tasks by a supervisory human operator. The demonstrator also provides a full bilateral force-reflecting hand control teleoperations capability. The operator may switch smoothly between the automated and teleoperated tasking modes in run-time, either on a preplanned or operator-designated basis.

Schenker, P. S.↗

Optimal Operation for Resilient and Economic Modes in an Islanded Alaskan Grid: Preprint

Power System is a complex system, with an objective to provide power to the customers. The objective is driven by a complex consideration of the secure, economic and resilient operation of the system. With the growing occurrence of extreme events emphasis has been shifted towards making the grid more resilient. However, an economic operation is still a priority for the utilities as well as its customers. Many utilities especially small isolated micro-grids do not emphasize much on an economic and resilient operation, but more on reliability. In this research we focus on striking a balance between economic and resilientoperation, ensuring reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

FFTSF: Revisiting Sub-Seasonal Streamflow Forecasting with Simple Feedforward Network

Accurate short-to-subseasonal streamflow forecasts are vital for water management, including flood preparedness, drought mitigation, hydropower scheduling, and ecosystem protection. However, extending a forecast beyond a few days remains challenging due to complexity of hydrological processes. While recent self-attention based transformer architectures such as iTransformer have gained traction in time-series forecasting, these models suffer from several critical limitations: (1) significant computational overhead that scales quadratically with sequence length, (2) vulnerability to overfitting on limited hydrological datasets, (3) degraded performance on long-horizon forecasts due to attention decay, and (4) excessive architectural complexity that hampers interpretability and operational deployment. In this study, we propose a simple Feedforward Time Series Forecasting (FFTSF) network that directly addresses these limitations through its lightweight architecture and long-range forecasting capabilities. We evaluate FFTSF across 178 USGS stream gauges spanning diverse climate regimes by forecasting lead times of 1-, 7-, 14-, and 30-days. Our results demonstrate that FFTSF achieves competitive performance at short lead times (NSE of 0.778 for 1-day forecasts) while substantially outperforming complex baselines at longer forecast period, achieving the highest NSE (0.271) at 30-day forecasts with greater robustness and stability. For 30-day forecasts, FFTSF achieves a 71% improvement over NLinear, 57% improvement over DLinear and 12% improvement over the computationally intensive iTransformer while requiring fewer computational resources. Our findings reveal that architectural complexity is not necessary for hydrological forecasting, demonstrating that well-designed simple models can outperform attention mechanisms for subseasonal streamflow forecasting. The computational efficiency and consistent long-range performance of FFTSF make it suitable for water management applications where reliable extended forecasts are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗

Binary Complex Neural Network Acceleration on FPGA

Being able to learn from complex data with phase information is imperative for many signal processing applications. Today’s real-valued deep neural networks (DNNs) have shown efficiency in latent information analysis but fall short when applied to the complex domain. Deep complex networks (DCN) , in contrast, can learn from complex data, but have high computational costs; therefore, they cannot satisfy the instant decision making requirements of many deployable systems dealing with short observations or short signal bursts. Recent, Binarized Complex Neural Network (BCNN), which integrates DCNs with binarized neural networks (BNN), shows great potential in classifying complex data in real-time. In this paper, we propose a structural pruning based accelerator of BCNN, which is able to provide more than 5000 frames/s inference throughput on edge devices. The high performance comes from both the algorithm and hardware sides. On the algorithm side, we conduct structural pruning to the original BCNN models and obtain 20 × pruning rates with negligible accuracy loss; on the hardware side, we propose a novel 2D convolution operation accelerator for the binary complex neural network. Experimental results show that the proposed design works with over 90% utilization and is able to achieve the inference throughput of 5882 frames/s and 4938 frames/s for complex NIN-Net and ResNet-18 using CIFAR-10 dataset and Alveo U280 Board.

Peng, Hongwu↗

Coupling a Computational Fluid Dynamics Model to a Spacecraft Thermal System Model for the DraMS Instrument Thermal Analysis

The Dragonfly Mass Spectrometer (DraMS) is an instrument on the Dragonfly mission, which will spend 7 years in deep space cruise before landing and operating on the surface of Titan. Vacuum thermal analyses are required for deep space cruise, and convection analyses are required for the Titan surface operations. Model exchanges across multiple thermal teams are needed for all phases of the mission. For DraMS, Thermal Desktop® (TD) has been the main thermal analytical tool of choice due to its capability in modeling complex thermal systems with relatively low computational power and for its availability across thermal teams. However, TD does not have computational fluid dynamics (CFD) capability and struggles to accurately capture complex convective behavior. DraMS has fans operating in tandem and gas flow behaviors are not easily predicted due to its complex flow paths. CFD software, such as Fluent, can model and predict such complex flow behaviors, but CFD models are computationally expensive, and its workflow processes are not tailored towards simulating large and complex systems. Therefore, a coupled modeling approach was chosen for DraMS: A TD model was used for simulating all the conductive, radiative, and source terms, while a Fluent CFD model was added on, as needed, to the TD model to provide the convective boundary conditions using the System Coupling software. The coupling software allows the TD and Fluent models to communicate data and arrive at a co-solved and co-converged solution. Furthermore, Thermal Iso-value Exchange (TIE) method was developed to facilitate and improve the TD-Fluent data exchange process. This paper will discuss the analytical studies that were done to verify the accuracy and usability of the coupled approach and the challenges associated, which lead to the development of the TIE approach. DraMS thermal design and co-solved analysis results will also be discussed.

Heat transfer↗

Coupling a Computational Fluid Dynamics (CFD) Model to a Spacecraft Thermal System Model for the DraMS Instrument Thermal Analysis

The Dragonfly Mass Spectrometer (DraMS) is an instrument on the Dragonfly mission, which will spend 7 years in deep space cruise before landing and operating on the surface of Titan. Vacuum thermal analyses are required for deep space cruise, and convection analyses are required for the Titan surface operations. Model exchanges across multiple thermal teams are needed for all phases of the mission. For DraMS, Thermal Desktop (TD) has been the main thermal analytical tool of choice due to its capability in modeling complex thermal systems with relatively low computational power and for its availability across thermal teams. However, TD does not have computational fluid dynamics (CFD) capability and struggles to accurately capture complex convective behavior. DraMS has fans operating in tandem and gas flow behaviors are not easily predicted due to its complex flow paths. CFD software, such as Fluent, can model and predict such complex flow behaviors, but CFD models are computationally expensive, and its workflow processes are not tailored towards simulating large and complex systems. Therefore, a coupled modeling approach was chosen for DraMS: A TD model was used for simulating all the conductive, radiative, and source terms, while a Fluent CFD model was added on, as needed, to the TD model to provide the convective boundary conditions using the System Coupling software. The coupling software allows the TD and Fluent models to communicate data and arrive at a co-solved and co-converged solution. Furthermore, Thermal Iso-value Exchange (TIE) method was developed to facilitate and improve the TD-Fluent data exchange process. This paper will discuss the analytical studies that were done to verify the accuracy and usability of the coupled approach and the challenges associated, which lead to the development of the TIE approach. DraMS thermal design and co-solved analysis results will also be discussed.

heat transfer↗

Governance and Resilience: A Holistic Approach to Systems Security in Complex and Chaotic Environments

Here, a systems governance approach emphasizes a holistic perspective that identifies and navigates the interdependencies and conflicts between security and operational needs. Governance is defined as a collection of metasystems that provide the necessary constraints and processes to support, steer, adapt, transform, and sustain a system (Keating et al. 2022). Utilizing the Cynefin framework, which distinguishes between simple, complicated, complex, and chaotic environments (Snowden and Boone 2007), the article highlights the challenges faced by nuclear power plants in predatory contexts and the importance of integrating security objectives into governance frameworks. By incorporating security as a fundamental aspect of governance, the article underscores its significance for persistence, adaptation, and transformation in the face of uncertainty. Additionally, it introduces key heuristics of systems security, such as the importance of context, knowledge‐based decision‐making, and organization‐specific sociological factors (Williams and Caskey 2024). Ultimately, this work provides valuable insights into enhancing resilient operations in complex environments by reinforcing the connection between effective governance and security in systems engineering.

Caskey, Susan A. [Sandia National Laboratories (SN↗

Operator origin of anomalous dimensions in de Sitter space

The late-time limit of the power spectrum for heavy (principal series) fields in de Sitter (dS) space yields a series of polynomial terms with complex scaling dimensions. Such scaling behavior is expected to result from an associated operator with a complex dimension. In a free theory, these complex dimensions are known to match the constraints imposed by unitarity on the space of states. Yet, perturbative corrections to the scaling behavior of operators are naively inconsistent with unitary evolution of the quantum fields in dS space. This paper demonstrates how to compute one-loop corrections to the scaling dimensions that appear in the two-point function from the field theory description in terms of local operators. We first show how to evaluate these anomalous dimensions using Mellin space, which has the feature that it naturally accommodates a scaleless regulator. We then explore the consequences for the soft de Sitter effective theory (SdSET) description that emerges in the long wavelength limit. Carefully matching between the UV and SdSET descriptions requires the introduction of novel nondynamical “operators” in the effective theory. This is not only necessary to reproduce results extracted from the Källén-Lehmann representation (that use the space of unitary states directly), but it is also required by general arguments that invoke positivity. Published by the American Physical Society 2025

Cohen, Timothy↗

Progressive autonomy

The present investigation is concerned with the evolution of a space station in terms of the progression of autonomy, as systems perspectives and architectural concepts permit. The distinction between automation and autonomy is considered along with the evolution of autonomy, and the evolution of automation in station operations. Attention is given to the startup of a complex technological system, aspects of station control, questions of crew operational support, factors regarding the habitability of a space station, system design philosophy for autonomy, evolvability, latent capability, stage commonality, and multiple modularity. It is concluded that an evolutionary space station operating over a period of 10-20 years with a great increase in capability over that time will require a design philosophy which is more flexible and open-ended than for previous space systems.

Anderson, J. L.↗

Planning and Estimation of Operations Support Requirements

Life Cycle Cost (LCC) estimates during the proposal and early design phases, as well as project replans during the development phase, are heavily focused on hardware development schedules and costs. Operations (phase E) costs are typically small compared to the spacecraft development and test costs. This, combined with the long lead time for realizing operations costs, can lead to de-emphasizing estimation of operations support requirements during proposal, early design, and replan cost exercises. The Discovery and New Frontiers (D&NF) programs comprise small, cost-capped missions supporting scientific exploration of the solar system. Any LCC growth can directly impact the programs' ability to fund new missions, and even moderate yearly underestimates of the operations costs can present significant LCC impacts for deep space missions with long operational durations. The National Aeronautics and Space Administration (NASA) D&NF Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for 5 missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that 4 out of the 5 missions studied had significant overruns at or after launch due to underestimation of the complexity and supporting requirements for operations activities; the fifth mission had not launched at the time of the mission. The drivers behind these overruns include overly optimistic assumptions regarding the savings resulting from the use of heritage technology, late development of operations requirements, inadequate planning for sustaining engineering and the special requirements of long duration missions (e.g., knowledge retention and hardware/software refresh), and delayed completion of ground system development work. This paper updates the D&NF LCC study, looking at the operations (phase E) cost drivers in more detail and extending the study to include 2 additional missions and identifies areas for increased emphasis by project management in order to improve the fidelity of operations estimates.

Newhouse, Marilyn E.↗

The Space Flight Operations Center first phase - Lessons learned

This paper is a retrospective look at the Space Flight Operations Center Project; a large, complex, multimission ground data system which is currently under development at the Jet Propulsion Laboratory (JPL), Pasadena. The Project was established in February 1984 and will be completed in April 1992 when the Magellan, Voyager, Ulysses, Galileo and Mars Observer Projects will be fully supported. The first phase of this project covers the development of a subset of multimission Baseline subsystems, the development of the mission-specific adaptations to this Baseline set for the Magellan Project, the development of a Magellan-specific high rate processor together with the delivery of these subsystems to operations. This first phase became operational in January 1989 in readiness for the Magellan launch in May 1989.

Gainsborough, A. J.↗

Microgravity Research Results and Experiences from the NASA Mir Space Station Program

The Microgravity Research Program Office (MRPO) participated aggressively in Phase I of the International Space Station Program using the Russian Mir Space Station. The Mir Station offered an otherwise unavailable opportunity to explore the advantages and challenges to long duration microgravity space research. Payloads with both NASA and commercial backing were included as well as cooperative research with the Canadian Space Agency (CSA). From this experience, much was learned about dealing with long duration on orbit science utilization and developing new working relationships with our Russian partner to promote efficient planning, operations, and integration to solve complexities associated with a multiple partner program. Microgravity participation in the NASA Mir Program began with the first joint NASA Mir flight to the Mir Space Station. The earliest participation setup acceleration measurement capabilities that were used throughout the Program. Research, conducted by all Microgravity science disciplines, continued on each subsequent increment for the entire three-year duration of the Program. The Phase I Program included the Microgravity participation of over 30 Fluids, Combustion, Materials, and Biotechnology Sciences and numerous commercially sponsored research payloads. In addition to the research gained from Microgravity investigations, long duration operation of facility hardware was tested. Microgravity facilities operated on Mir included the Space Acceleration Measurement System (SAMS), the Microgravity Glovebox (MGBX), the Biotechnology System (BTS) and the Canadian Space Agency sponsored Microgravity Isolation Mount (MIM). The Russian OPTIZONE Furnace was also incorporated into our material science research. All of these efforts yielded significant and useful scientific research data. This paper focuses on the microgravity research conducted onboard the Mir space station. It includes the Program preparation and planning necessary to support this type of cross increment research experience; the payloads which were flown; and summaries of significant microgravity science findings. Most importantly this paper highlights the various disciplines of microgravity research conducted during the International Space Station, Phase 1 Program onboard the Mir Station. A capsulation of significant research and the applicability of our findings are provided. In addition, a brief discussion of how future microgravity science gathering capabilities, hardware development and payload operations techniques have enhanced our ability to conduct long duration microgravity research.

Schagheck, R. A.↗

Test, Control and Monitor System (TCMS) operations plan

The purpose is to provide a clear understanding of the Test, Control and Monitor System (TCMS) operating environment and to describe the method of operations for TCMS. TCMS is a complex and sophisticated checkout system focused on support of the Space Station Freedom Program (SSFP) and related activities. An understanding of the TCMS operating environment is provided and operational responsibilities are defined. NASA and the Payload Ground Operations Contractor (PGOC) will use it as a guide to manage the operation of the TCMS computer systems and associated networks and workstations. All TCMS operational functions are examined. Other plans and detailed operating procedures relating to an individual operational function are referenced within this plan. This plan augments existing Technical Support Management Directives (TSMD's), Standard Practices, and other management documentation which will be followed where applicable.

Macfarlane, C. K.↗

Intent inferencing by an intelligent operator's associate - A validation study

In the supervisory control of a complex, dynamic system, one potential form of aiding for the human operator is a computer-based operator's associate. The design philosophy of the operator's associate is that of 'amplifying' rather than automating human skills. In particular, the associate possesses understanding and control properties. Understanding allows it to infer operator intentions and thus form the basis for context-dependent advice and reminders; control properties allow the human operator to dynamically delegate individual tasks or subfunctions to the associate. This paper focuses on the design, implementation, and validation of the intent inferencing function. Two validation studies are described which empirically demonstrate the viability of the proposed approach to intent inferencing.

Jones, Patricia M.↗

On Bellman’s and Knuth’s Problems and their Generalizations

Various generalizations of the classical problem of the fastest raising to a power (or the so-called problem on addition chains) are studied in the asymptotic sense. Under weak restrictions, we demonstrate asymptotically tight solutions of the two best known generalizations, namely, Bellman’s problem on the computational complexity (on the minimal number of multiplication operations) of a normed monomial of several variables and Knuth’s problem on the computational complexity of a power system of one variable. We also briefly review some results on the computational complexity for three problems, namely, the computation of p-element systems of normed monomials in q variables, additive computations for systems of p integer linear forms over q variables, and the computation of p-element systems of the free Abelian group with q generators.

97 MATHEMATICS AND COMPUTING↗

Engine Operating Conditions, Fuel Property Effects, and Associated Fuel–Wall Interaction Dependencies of Stochastic Preignition

This work for the Coordinating Research Council (CRC) explores dependencies on the opportunity for fuel to impinge on internal engine surfaces (i.e., fuel–wall impingement) as a function of fuel properties and engine operating conditions and correlates these data with measurements of stochastic preignition (SPI) propensity. SPI rates are directly coupled with laser–induced florescence measurements of dye-doped fuel dilution measurements of the engine lubricant, which provides a surrogate for fuel–wall impingement. Literature suggests that SPI may have several dependencies, one being fuel–wall impingement. However, it remains unknown if fuel-wall impingement is a fundamental predictor and source of SPI or is simply a causational factor of SPI. In this study, these relationships on SPI and fuel-wall impingement are explored using 4 fuels at 8 operating conditions per fuel, for 32 total test points. The fuels were directly injected at two different injection timings: an earlier injection timing that initially targets the piston crown and a later injection timing that targets the cylinder liner. At each injection timing, the engine was operated at both 90°C and 70°C coolant and lubricant temperatures, and 185 and 200 kPa absolute intake manifold pressure. This work serves as an exploratory effort to down select conditions and provide initial fuel properties of interest for a secondary study to explore fuel property specific effects on fuel-wall interaction and SPI propensity. Significant findings from this initial operating condition and fuel property exploratory work are: 1. reduced engine operating coolant and lubricant temperatures, along with 2. retarded injection timings were required to increase SPI propensity. Moreover, at these conditions some fuel specific effects were also observed; specifically, increased ethanol content increased measured dye–wall (i.e., fuel–wall) interaction. However, despite increased dye–wall interaction, the increased volatility of the ethanol containing fuels also reduced the estimated fuel retention in the top-ring zone and associated measured SPI propensity. Thus, the findings of this unique approach to explore relationships between fuel-wall impingement and SPI highlight that SPI propensity is more directly proportional to retained fuel, and not simply fuel–wall impingement. Furthermore, fuel retention was found to be directly influenced by complex fuel property and engine operating condition relationships. Either retarded injection timings and/or increased fuel volatility increased fuel wall-impingement, while less volatile fuels and/or reduced coolant temperatures increased fuel retention. Therefore, for a given operating condition, the data highlights that greater volatile fuels exhibit increased fuel wall impingement without increased fuel retention or SPI propensity, while less volatile fuels could exhibit reduced fuel-wall impingement but increased fuel retention and SPI propensity rates.

33 ADVANCED PROPULSION SYSTEMS↗

ATTRACTOR: Toward Trustworthy and Trusted Autonomous Systems

The question of what it means and what it takes for an autonomous system to consider another autonomous system justifiably trustworthy must be addressed by all who seek to integrate intelligent machine agents into real-world operations. A satisfactory answer to this question is an essential component in accepting autonomous machine decision-making in safety-critical and time-critical environments, such as aviation. Historically, simulation platforms for test and evaluation of complex systems have proven to be effective in assessing performance and contributing to decisions on the fitness of systems to operate in current general and commercial aviation airspace. Moreover, simulations have informed the definition of safety-critical constraints. However, as machine systems progressively take on responsibilities for decision-making traditionally supplied by humans, simulations require enhancement. Mixed reality simulation that integrates real-world platforms and data or high-fidelity simulation data in a sim-to-flight paradigm provides insight into agent interaction and the rationale behind autonomous agent decision-making as well as the capacity for seamless integrated implementation, testing, and operation of systems. Strong simulation capabilities are especially important in the presence of algorithms that hold great promise in decision-making yet increase the uncertainty in the system. Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) is a subproject of NASA’s Convergent Aeronautics Solutions (CAS) Project. ATTRACTOR’s objective is to build a basis for understanding trust and trustworthiness in multi-agent autonomous teams, and thus to inform future certification of safety-critical and time-critical autonomous systems in aviation. Because the concepts of trust and trustworthiness must be addressed in a context, ATTRACTOR has chosen Search and Rescue (SAR) in dynamic and unstructured environments, with emphasis on search, as its design reference mission (DRM). During dynamic planning and execution of trajectory-based operations, autonomous agents determine their trajectories given an assigned mission or missions and call for assistance from an appropriate teammate when needed. This experience along with the attendant human-machine and machine-machine interactions, serve as a platform for developing approaches to identifying and measuring trustworthiness and increasing trust. In this paper, we give an overview of some of ATTRACTOR’s research and development activities, findings, and ongoing work.

ATTRACTOR↗

Quick Cooling and Filling Through a Single Port for Cryogenic Transfer Operations

Improved technology for the efficient transfer of cryogens is needed for future on-orbit fueling and remote Lunar/Mars operations. The cooling and filling of a liquid nitrogen (LN2) test vessel through a single port were investigated in a series of experiments. A new 'in-space' transfer tube design concept was used to demonstrate the ability to quickly cool and load cryogens through a single feed-through connection. Three different fill tube configurations with three different diameters were tested. The tubes providing the quickest cooldown time and the quickest fill time for the test article tank were determined. The results demonstrated a clear trade-off between cooling time and filling time for the optimum tube design. This experimental study is intended to improve technology for future flight tank designs by reducing fill system size, complexity, heat leak rate, and operations time. These results may be applied to Space Shuttle Power Reactant Storage and Distribution (PRSD) System upgrades and other future applications. Further study and experimental analysis for optimization of the fill tube design are in progress.

Jones, J. R.↗