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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 307 records · Page 17

A multiple access communication network based on adaptive arrays

A single frequency communication system is considered consisting of K possibly moving users distributed in space simultaneously communicating with a central station equipped with a computationally adapted array of n = or K antennas. Such a configuration could result if K spacecraft were to be simultaneously tracked by a single DSN complex consisting of an n antennas array. The array employs K sets of n weights to segregate the signals received from the K users. The weights are determined by direct computation based on known position information of the K users. Currently known techniques require (for n = K) about (4/3)K to the 4th power computer operations (multiply and add) to perform such computations. A technique that accomplishes this same goal in 8 K to the 3rd power operations, yielding a reduction by a factor K/6, was developed.

Zohar, S.↗

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗

Expectations of Future Natural Hazards in Human Adaptation to Concurrent Extreme Events in the Colorado River Basin

Human adaptation to climate change is the outcome of long-term decisions continuously made and revised by local communities. Adaptation choices can be represented by economic investment models in which the often large upfront cost of adaptation is offset by the future benefits of avoiding losses due to future natural hazards. In this context, we investigate the role that expectations of future natural hazards have on adaptation in the Colorado River basin of the USA. We apply an innovative approach that quantifies the impacts of changes in concurrent climate extremes, with a focus on flooding events. By including the expectation of future natural hazards in adaptation models, we examine how public policies can focus on this component to support local community adaptation efforts. Findings indicate that considering the concurrent distribution of several variables makes quantification and prediction of extremes easier, more realistic, and consequently improves our capability to model human systems adaptation. Hazard expectation is a leading force in adaptation. Even without assuming increases in exposure, the Colorado River basin is expected to face harsh increases in damage from flooding events unless local communities are able to incorporate climate change and expected increases in extremes in their adaptation planning and decision making.

54 ENVIRONMENTAL SCIENCES↗

TBASS: A Robust Adaptation of Bayesian Adaptive Spline Surfaces

The R package TBASS is an extension of the BASS package created by Francom and Sansó (2019). The package is used to fit a Bayesian multivariate adaptive spline to a dataset that either follows a Student’s t-distribution or has outliers. Much of the framework for TBASS is adapted from the concepts of Bayesian Multivariate Adaptive Regression Splines (BMARS), specifically the work done by Denison, Mallick, and Smith (1998). The spline function is fit using a Reversible-Jump Markov Chain Monte Carlo algorithm,. By including this more robust generalization, a dataset with outliers can be accurately fit using the BMARS model, without the possibility of overfitting or variance inflation.

97 MATHEMATICS AND COMPUTING↗

Burning questions for a warming and changing world: 15 unknowns in plant abiotic stress

Abstract We present unresolved questions in plant abiotic stress biology as posed by 15 research groups with expertise spanning eco-physiology to cell and molecular biology. Common themes of these questions include the need to better understand how plants detect water availability, temperature, salinity, and rising carbon dioxide (CO2) levels; how environmental signals interface with endogenous signaling and development (e.g. circadian clock and flowering time); and how this integrated signaling controls downstream responses (e.g. stomatal regulation, proline metabolism, and growth versus defense balance). The plasma membrane comes up frequently as a site of key signaling and transport events (e.g. mechanosensing and lipid-derived signaling, aquaporins). Adaptation to water extremes and rising CO2 affects hydraulic architecture and transpiration, as well as root and shoot growth and morphology, in ways not fully understood. Environmental adaptation involves tradeoffs that limit ecological distribution and crop resilience in the face of changing and increasingly unpredictable environments. Exploration of plant diversity within and among species can help us know which of these tradeoffs represent fundamental limits and which ones can be circumvented by bringing new trait combinations together. Better defining what constitutes beneficial stress resistance in different contexts and making connections between genes and phenotypes, and between laboratory and field observations, are overarching challenges.

Biochemistry & Molecular Biology↗

Ubiquitous Power Electronics in Future Power Systems: Recommendations to fully utilize fast control capabilities

Power electronics is becoming ubiquitous in power systems because the rapid growth of variable renewable generation such as wind and solar, responsive load, electric vehicles, energy storage, as well as DC transmission. As a result, a high percentage of electricity will be generated, transmitted or consumed by power electronics in the future power system. Such a high penetration of power electronics is changing power system operation landscapes and dynamic characteristics. Two major kinds of impact are reduced system mechanical inertia by inverter-based resources displacing conventional generation and active participation of many distributed energy resources through inverters. This has caused significant reliability challenges for power system operation. The mitigation approach so far has mostly focused on accommodating power electronics inverters as passive devices or creating synthetic inertias to make inverter-based generation behaving as conventional generators. However, the high-speed control capabilities of power electronics present new opportunities for achieving an optimal performance beyond conventional power systems. A lower-inertia system can be more responsive for improving reliability, and distributed small resources can be more adaptive and scalable for better flexibility and resilience. Power electronic inverters are capable of multiple fast control functions. To fully utilized the ubiquitous power electronics in power systems requires technology advancements in the following areas: data and communications to capture the new dynamic behaviors introduced by power electronics; modeling and simulation to understand the behaviors of power electronics and its interactions with other components in the context of power systems; control and optimization methods for fully utilizing the capabilities of power electronics for a new paradigm of performance beyond the traditional inertia-heavy system; and significant upgrades in power electronics hardware to cater to the new control capabilities. If properly controlled and optimized, power electronics can help transform the power system to be responsive, adaptive, and scalable.

Huang, Zhenyu↗

Current possibilities and future opportunities for erasure coded computations

The key capability established through the research funded by this award are erasure coded computations for linear systems, in serial and in parallel. This capability enables powerful efficient and scalable alternatives to existing linear system solvers in fault-prone computational systems.

97 MATHEMATICS AND COMPUTING↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

5G integrated edge computing platform for efficient component monitoring in coal-fired power plants

This project developed a cutting-edge 5G-integrated edge computing framework to enhance operational efficiency and reliability in coal-fired power plants through real-time component monitoring and anomaly detection. The initiative focused on leveraging distributed machine learning, federated learning, and 5G-based dynamic network slicing to support scalable, fault-tolerant monitoring environments to meet the operational requirements in industrial control systems. With a Distributed Edge Computing Service (DECS) orchestration, this project enabled federated learning at edge for condition monitoring and introduced adaptive client selection strategies to minimize communication overhead. Scalable distributed training was achieved using the Horovod framework, thus enhancing performance across edge nodes. In the realm of 5G networking, the project designed and deployed reconfigurable, QoS-aware network slicing tailored for operational technology (OT) environments, integrating software-defined networks to bolster cyber-resilience and enabling dynamic slicing for federated learning workloads. A significant milestone was the development of a virtualized ICS environment with 5G core integration—which allowed elastic and fault tolerant distributed training on real-world datasets such as NASA Bearings, Hydraulic Systems, and TEP. To broaden the impact of the project, a TRL-3 virtualized ICS testbed for research and education was designed. This project engaged several graduate and undergraduate students to conduct research on the cutting-edge technology, and it resulted in one PhD dissertation, one MS thesis, and over 14 peer-reviewed publications. With the support of this project students also participated in national cybersecurity competitions to improve their professional development skills.

20 FOSSIL-FUELED POWER PLANTS↗

Transfer-matrices for series-type microwave antenna circuits

Transfer matrices are developed which permit analysis and computer evaluation of certain series type microwave antenna circuits associated with an L-Band microwave radiometer (LBMR) under investigation at Goddard Space Flight Center. This radiometer is one of several diverse instrument designs to be used for the determination of soil moisture, sea state, salinity, and temperature data. Four port matrix notation is used throughout for the evaluation of LBMR circuits with mismatched couplers and lossy transmission lines. Matrix parameters in examples are predicted on an impedance analysis and an assumption of an array aperture distribution. The notation presented is easily adapted to longer and more varied chains of matrices, and to matrices of larger dimension.

Schmidt, R. F.↗

High level continuity for coordinate generation with precise controls

Coordinate generation techniques with precise local controls have been derived and analyzed for continuity requirements up to both the first and second derivatives, and have been projected to higher level continuity requirements from the established pattern. The desired local control precision was obtained when a family of coordinate surfaces could be uniformly distributed without a consequent creation of flat spots on the coordinate curves transverse to the family. Relative to the uniform distribution, the family could be redistributed from an a priori distribution function or from a solution adaptive approach, both without distortion from the underlying transformation which may be independently chosen to fit a nontrivial geometry and topology.

Eiseman, P. R.↗

Flexible structure control laboratory development and technology demonstration

An experimental structure is described which was constructed to demonstrate and validate recent emerging technologies in the active control and identification of large flexible space structures. The configuration consists of a large, 20 foot diameter antenna-like flexible structure in the horizontal plane with a gimballed central hub, a flexible feed-boom assembly hanging from the hub, and 12 flexible ribs radiating outward. Fourteen electrodynamic force actuators mounted to the hub and to the individual ribs provide the means to excite the structure and exert control forces. Thirty permanently mounted sensors, including optical encoders and analog induction devices provide measurements of structural response at widely distributed points. An experimental remote optical sensor provides sixteen additional sensing channels. A computer samples the sensors, computes the control updates and sends commands to the actuators in real time, while simultaneously displaying selected outputs on a graphics terminal and saving them in memory. Several control experiments were conducted thus far and are documented. These include implementation of distributed parameter system control, model reference adaptive control, and static shape control. These experiments have demonstrated the successful implementation of state-of-the-art control approaches using actual hardware.

Vivian, H. C.↗

Intelligent multi-sensor integrations

Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.

Volz, Richard A.↗

A dynamic study of fragmentation and energy loss during high velocity impact

Research conducted under this contract can be divided into two main areas: hypervelocity (in the range up to 7 km/s) and high velocity (less than 1 km/s). Work in the former was performed at NASA-MSFC using the Light Gas Gun Facility. The lower velocity studies were conducted at Auburn University using the ballistic gun. The emphasis of the project was on the hypervelocity phenomenon especially in the characterization of the debris cloud formed by the primary impact events. Special devices were made to determine the angular distributions of momentum and energy of the debris cloud as a function of impact conditions. After several iteration processes, it was decided to concentrate on the momentum effort. Prototype devices were designed, fabricated, and tested. These devices were based on the conservation of momentum. Distributions of the debris cloud formed were measured by determining the amount of momentum transferred from the debris cloud to strategically placed pendulum measurement devices. The motion of the pendula was monitored using itegrated opto-interrupters. The distribution of momentum in the debris cloud was found to be a strong function of the impact condition. Small projectiles at high velocities were observed to produce finely dispersed debris whereas large projectiles generated discrete particles in the debris. Results also show that the momentum in the forward direction was enhanced due to the impact. This phenomenon of momentum multiplication was also observed in other studies and in computer simulations. It was initially planned to determine the energy distribution using deformation energy in a rod with strain gauges. Results from preliminary studies show that this technique is acceptable but too tedious. A new technique was explored based on measuring the heating effect of the debris cloud using an IR camera. The feasibility and sensitivity was established at Auburn University. This type of energy distribution measurement method can easily be adapted to the gas gun facility at MSFC. The objective of the lower velocity studies at Auburn was to simulate the damage produced in advanced materials by the lower energy debris cloud.

Zee, Ralph H.↗

On adaptive weighted polynomial preconditioning for Hermitian positive definite matrices

The conjugate gradient algorithm for solving Hermitian positive definite linear systems is usually combined with preconditioning in order to speed up convergence. In recent years, there has been a revival of polynomial preconditioning, motivated by the attractive features of the method on modern architectures. Standard techniques for choosing the preconditioning polynomial are based only on bounds for the extreme eigenvalues. Here a different approach is proposed, which aims at adapting the preconditioner to the eigenvalue distribution of the coefficient matrix. The technique is based on the observation that good estimates for the eigenvalue distribution can be derived after only a few steps of the Lanczos process. This information is then used to construct a weight function for a suitable Chebyshev approximation problem. The solution of this problem yields the polynomial preconditioner. In particular, we investigate the use of Bernstein-Szego weights.

Fischer, Bernd↗

Introductory Remarks

Future vehicle designs will see a paradigm shift from: 1) Steady to the unsteady world (e.g. flow control, adaptive morphing); 2) Passive to active; 3) Rigid designs to exploitation of flexibility and adaptability; 4) Few discrete to numerous distributed (e.g. sensors, control surfaces); 5) To obtain a vehicle that is always at optimum performance. Therefore, future designs will be inherently multidisciplinary, and the greatest technical challenges and opportunities occur at the intersection of disciplines COMSAC appears to be a step towards enabling the future vision.

Tenney, Darrel R.↗