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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

A CLIPS prototype for autonomous power system control

The model of the system assumes a constant power source and loads (experiments) whose power demands exceed the supply. Experiments are described by their name, power consumption, time for a complete run, present status and the state of the load. The power consumption of each load is set at a constant level but can be dynamically modified by the operator. The status specifies if the experiment is running, paused, completed or failed. The state compensates for the lack of actual feedback sensor data, by signifying the stability of the load. Experiments are scheduled to keep as many running as possible with the current system limitations. A graphics oriented user interface is embedded into the rule-based system to enable an operator to easily experiment with the system.

Vezina, James M.↗
NASA NTRS2015

A Tool for Model-Based Generation of Scenario-driven Electric Power Load Profiles

Power consumption during all phases of spacecraft flight is of great interest to the aerospace community. As a result, significant analysis effort is exerted to understand the rates of electrical energy generation and consumption under many operational scenarios of the system. Previously, no standard tool existed for creating and maintaining a power equipment list (PEL) of spacecraft components that consume power, and no standard tool existed for generating power load profiles based on this PEL information during mission design phases. This paper presents the Scenario Power Load Analysis Tool (SPLAT) as a model-based systems engineering tool aiming to solve those problems. SPLAT is a plugin for MagicDraw (No Magic, Inc.) that aids in creating and maintaining a PEL, and also generates a power and temporal variable constraint set, in Maple language syntax, based on specified operational scenarios. The constraint set can be solved in Maple to show electric load profiles (i.e. power consumption from loads over time). SPLAT creates these load profiles from three modeled inputs: 1) a list of system components and their respective power modes, 2) a decomposition hierarchy of the system into these components, and 3) the specification of at least one scenario, which consists of temporal constraints on component power modes. In order to demonstrate how this information is represented in a system model, a notional example of a spacecraft planetary flyby is introduced. This example is also used to explain the overall functionality of SPLAT, and how this is used to generate electric power load profiles. Lastly, a cursory review of the usage of SPLAT on the Cold Atom Laboratory project is presented to show how the tool was used in an actual space hardware design application.

power load profile↗
DOE OSTI2024

Power Analysis of an ePump Applied to the Linear Functions of an Agricultural Planter

Like many other industries, the agricultural industry has recently ex-perienced pressure to reduce vehicle emissions while improving productivity. Electric actuation is perceived as a viable solution to replace or augment hydrau-lic and mechanical actuation. However, electrification presents challenges with regards to linear functions, where hydraulic actuators have advantages in terms of compactness, tolerance to contamination and resistance to shocks. A combined electro-hydraulic actuation architecture can leverage the benefits of both electric and hydraulic actuation, while reducing the drawbacks of both approaches. This work investigates the potential of a centralized electric driven pump (ePump) system powering the pressure-controlled linear functions of an agricul-tural planter, with the goal of improving the operating point of the main supply pump. In this application, the rotary functions are hydraulically actuated, alt-hough such a solution could be applied also to electric rotary actuation. This is accomplished by setting the ePump to boost the pressure supplied by the tractor to the level required by the linear functions. An accumulator is used to stabilize the flow requirements of the linear functions, and control the pressure supplied to the actuators. Two control schemes are proposed for the regulation of the ac-cumulator pressure, one favoring an efficient operating point for the ePump, the other favoring stable steady state operation. A simulation model of the baseline system and proposed system is developed and validated using experimental data from a full-scale machine. Using the vali-dated simulation, both control architectures are then evaluated for improvement in system power consumption and dynamic requirements on the ePump to assess their effectiveness. Both systems demonstrate significant improvement in power consumption over the baseline system, with the best solution improving effi-ciency by 64%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Load Disaggregation (Modeling Individual Appliance Power Generation & Consumption in Real-Time)

We developed a machine learning-based load disaggregation method to estimate the real-time output of individual appliances from the whole-house measurements. We first learn the important features associated with each type of appliances using the ground truth consumption data of individual appliances potentially available for a small set of houses equipped with submeters. The learned features are then be used to estimate the power generation/consumption of the appliances from the whole-house consumption. This developed load disaggregation software includes two steps. The first step is to identify the on/off status of different appliances using a classification method, and the second step is to estimate the appliance output using a regression method.

Hao, Jun↗
DOE OSTI2022

Peak Power Minimization for Commercial Thermostatically Controlled Loads in Multi-Unit Grid-Interactive Efficient Buildings

The load profiles of most commercial and industrial consumers are characterized by brief periods of very high power consumption followed by intervals of lower demand. To encourage such consumers to flatten their load profiles, power utilities in and around the world often levy a monthly demand charge (DC) on the peak demand measured over brief intervals. In this work, we consider the joint optimization of energy costs (EC) and the instantaneous peak power of a multi-unit building which uses a hydronic heating, ventilation and cooling (HVAC) system and responds to a demand response (DR) program. Despite the non-linear structure of the problem, we show how optimal solutions can be obtained efficiently using linear programming. Next, we study the power demand patterns resulting from our proposed strategy for thermostatically controlled loads (TCLs), and evaluate the strategy’s performance for various climate zones in the US, under both typical and atypical weather conditions. Finally, the results show that depending on the ambient conditions and the tariff structure, our strategy can result in utility bill savings of up to nearly 19% compared to the baseline. The results also indicate that our power control strategy can significantly reduce the instantaneous peak power consumption in commercial TCLs.

HVAC↗
DOE OSTI2021

Energy use of residential safety, security, and health devices

Miscellaneous electrical loads (MELs) are responsible for a significant fraction of energy consumption in buildings. This paper addresses one category of MELs: Safety, Security, and Health Devices (SSHDs). Common SSHDs include: electrical life safety equipment, smoke alarms, radon mitigation fans, and home oxygen concentrators. The installation or use of these devices is dictated by building codes, health providers, insurance companies, and other entities—none of which would ordinarily consider energy efficiency a priority. For this project, the most important residential devices were explored in terms of their governing regulations, functions, technologies, and energy use. The power consumption of 41 life safety SSHDs were measured. Individual power consumption of life safety devices is very small but many are typically required in every home. Devices performing the same functions have wide ranges in power use. Opportunities for reducing SSHD energy use were investigated, the results are summarized, and recommendations are made for further actions that could be taken to reduce SSHD energy use. Finally, SSHDs identified in this paper are responsible for at least one percent of current U.S. residential electricity consumption, but that number will climb steadily as existing buildings are upgraded and new types of SSHDs appear.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1993

Mars laser altimeter based on a single photon ranging technique

The Mars 94/96 Mission will carry, among others things, the balloon probe experiment. The balloon with the scientific cargo in the gondola underneath will drift in the Mars atmosphere, its altitude will range from zero, in the night, up to 5 km at noon. The accurate gondola altitude will be determined by an altimeter. As the Balloon gondola mass is strictly limited, the altimeter total mass and power consumption are critical; maximum allowed is a few hundred grams a few tens of mWatts of average power consumption. We did propose, design, and construct the laser altimeter based on the single photon ranging technique. Topics covered include the following: principle of operation, altimeter construction, and ground tests.

Prochazka, Ivan↗
DOE OSTI2021

Characterization of the CMS Endcap Timing Layer readout chip prototype with charge injection

We present the characterization of a readout Application-Specific Integrated Circuit (ASIC) for the CMS Endcap Timing Layer (ETL) of the High-Luminosity LHC upgrade with charge injection. The ASIC, named ETROC and developed in a 65 nm CMOS technology, reads out a 16× 16 pixel matrix of the Low-Gain Avalanche Detector (LGAD). The jitter contribution from ETROC is required to be below 40 ps to achieve the 50 ps overall time resolution per hit. The analog readout circuits in ETROC consist of the preamplifier and the discriminator. The preamplifier handles the LGAD charge signal with the most probable value of around 15 fC. The discriminator generates the digital pulse, which provides the Time-Of-Arrival (TOA, leading edge) and Time-Over-Threshold (TOT, pulse width) information. The prototype of ETROC (ETROC0) that implements a single channel of analog readout circuits has been evaluated with charge injection. The jitter of the analog readout circuits, measured from the discriminator's leading edge, is better than 16 ps for a charge larger than 15 fC with the sensor capacitance. The time walk resulting from different pulse heights can be corrected using the TOT measurement. The time resolution distribution has a standard deviation of 29 ps after the time-walk correction from the charge injection. At room temperature, the preamplifier's power consumption is measured to be 0.74 mW and 1.53 mW per pixel in the low- and high-power mode, respectively. Finally, the measured power consumption of the discriminator is 0.84 mW per pixel. With the ASIC alone or the LGAD sensor, The characterization performances fulfill the ETL's challenging requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Empirically-calibrated H100 node power models for accurate AI training energy estimation

Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.

Newkirk, Alex C↗
NASA NTRS2010

A High-Throughput, Adaptive FFT Architecture for FPGA-Based Space-Borne Data Processors

Historically, computationally-intensive data processing for space-borne instruments has heavily relied on ground-based computing resources. But with recent advances in functional densities of Field-Programmable Gate-Arrays (FPGAs), there has been an increasing desire to shift more processing on-board; therefore relaxing the downlink data bandwidth requirements. Fast Fourier Transforms (FFTs) are commonly used building blocks for data processing applications, with a growing need to increase the FFT block size. Many existing FFT architectures have mainly emphasized on low power consumption or resource usage; but as the block size of the FFT grows, the throughput is often compromised first. In addition to power and resource constraints, space-borne digital systems are also limited to a small set of space-qualified memory elements, which typically lag behind the commercially available counterparts in capacity and bandwidth. The bandwidth limitation of the external memory creates a bottleneck for a large, high-throughput FFT design with large block size. In this paper, we present the Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture for a moderately large block size (32K) with considerations to power consumption and resource usage, as well as throughput. We will also show that the architecture can be easily adapted for different FFT block sizes with different throughput and power requirements. The result is completely contained within an FPGA without relying on external memories. Implementation results are summarized.

Nguyen, Kayla↗
DOE OSTI2025

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗
NASA NTRS1991

Low cost high efficiency GaAs monolithic RF module for SARSAT distress beacons

Low cost high performance (5 Watts output) 406 MHz beacons are urgently needed to realize the maximum utilization of the Search and Rescue Satellite-Aided Tracking (SARSAT) system spearheaded in the U.S. by NASA. Although current technology can produce beacons meeting the output power requirement, power consumption is high due to the low efficiency of available transmitters. Field performance is currently unsatisfactory due to the lack of safe and reliable high density batteries capable of operation at -40 C. Low cost production is also a crucial but elusive requirement for the ultimate wide scale utilization of this system. Microwave Monolithics Incorporated (MMInc.) has proposed to make both the technical and cost goals for the SARSAT beacon attainable by developing a monolithic GaAs chip set for the RF module. This chip set consists of a high efficiency power amplifier and a bi-phase modulator. In addition to implementing the RF module in Monolithic Microwave Integrated Circuit (MMIC) form to minimize ultimate production costs, the power amplifier has a power-added efficiency nearly twice that attained with current commercial technology. A distress beacon built using this RF module chip set will be significantly smaller in size and lighter in weight due to a smaller battery requirement, since the 406 MHz signal source and the digital controller have far lower power consumption compared to the 5 watt power amplifier. All the program tasks have been successfully completed. The GaAs MMIC RF module chip set has been designed to be compatible with the present 406 MHz signal source and digital controller. A complete high performance low cost SARSAT beacon can be realized with only additional minor iteration and systems integration.

Petersen, W. C.↗
DOE OSTI2020

An 85 nW IoT Node-Controlling SoC for MELs Power-Mode Management and Phantom Energy Reduction

This paper presents an ultra-low power (ULP) node-controlling system-on-chip (SoC) used for power-mode management and phantom energy reduction of miscellaneous electric loads (MELs). The SoC is powered from a single 2.5 V voltage supply enabled by the integrated power management unit (PMU) and can control up to 16 MELs due to the on-chip 16-channel correlator and the 32b RISC-V microprocessor. To further reduce the system power consumption, two clock domains have been adopted for the correlator and the processor separately. Fabricated in 65-nm CMOS, the measured minimum power consumption of the proposed SoC is only 85 nW at 0.45 V voltage supply and 1 kHz clock frequency. The measured maximum operating frequency can go up to 148 kHz with a 0.55 V supply. An application experiment successfully demonstrates that the SoC controls the power modes of MELs from wake-up to cut-off to save the average power and phantom energy.

power-mode management, phantom energy, phantom pow↗
NASA NTRS1974

Operating characteristics of 120-millimeter-bore ball bearings at 3 million DN

A parametric study was performed with split inner-race 120-mm-bore angular-contact ball bearings at a speed of 25,000 rpm (3 million DN) at initial contact angles of 20 deg and 24 deg. Provisions were made for outer- and inner-race cooling and for injection of lubricant into the bearing through a number of radial holes in the split inner-race of the bearing. Oil flow and coolant rate to the bearing was controlled and varied for a total up to approximately 3.2 gal/min. Bearing temperature was found to decrease as the total lubricant flow to the bearing increased. However, at intermediate flow rates temperature began to increase with increasing flow. Power consumption increased with increasing flow rate. Bearing operating temperature, differences in temperatures between the inner and outer races, and bearing power consumption can be tuned to any desirable operating requirement. Cage speed increased by not more than 2 percent with increasing oil flow to the inner race.

Zaretsky, E. V.↗
NASA NTRS2009

Small CO2 Sensors Operate at Lower Temperature

Solid-electrolyte-based amperometric sensors for measuring concentrations of CO2 in air are being developed for use in detection of fires, environmental monitoring, and other applications where liquid-based electrochemical cells are problematic. These sensors are small (sizes of the order of a millimeter), are robust, are amenable to batch fabrication at relatively low cost, and exhibit short response times (seconds) and wide detection ranges. A sensor of this type at a previous stage of development included a solid electrolyte of Na3Zr2Si2PO12 deposited mainly between interdigitated Pt electrodes on an alumina substrate, all overcoated with an auxiliary solid electrolyte of (Na2CO3:BaCO3 in a molar ratio of 1:1.7). It was necessary to heat this device to a temperature as high as 600 C to obtain the desired sensitivity and rapid response. Heating sensors increases the power consumption of the sensor system and complicates the use of the sensor in some applications. Thus, decreasing a sensor s power consumption while maintaining its performance is a technical goal of ongoing development.

Hunter, Gary W.↗
NASA NTRS2002

A Particle and Energy Balance Model of the Orificed Hollow Cathode

A particle and energy balance model of orificed hollow cathodes was developed to assist in cathode design. The model presented here is an ensemble of original work by the author and previous work by others. The processes in the orifice region are considered to be one of the primary drivers in determining cathode performance, since the current density was greatest in this volume (up to 1.6 x 10(exp 8) A/m2). The orifice model contains comparatively few free parameters, and its results are used to bound the free parameters for the insert model. Next, the insert region model is presented. The sensitivity of the results to the free parameters is assessed, and variation of the free parameters in the orifice dominates the calculated power consumption and plasma properties. The model predictions are compared to data from a low-current orificed hollow cathode. The predicted power consumption exceeds the experimental results. Estimates of the plasma properties in the insert region overlap Langmuir probe data, and the predicted orifice plasma suggests the presence of one or more double layers. Finally, the model is used to examine the operation of higher current cathodes.

Domonkos, Matthew T.↗
DOE OSTI2021

Heterogeneous network topology management and control

In one aspect, the present disclosure may provide devices or systems configured to receive indications of geographic areas, each corresponding to distribution networks, and determine whether the distribution networks overlap. The processor(s) may also be configured to receive parameter value(s) obtained by a device within one distribution network at a location within an overlapping area, and cause device(s) within another distribution network to modify operation based on the parameter value(s). In another aspect, the present disclosure may provide devices that include a voltage sensor to measure a voltage of a power distribution network at a power consumption location that corresponds to the device. The device may be configured to provide at least one cable service to the power consumption location via a cable television (CATV) distribution network and output an indication the measured voltage value.

Cruickshank, III, Robert Fraser↗
NASA NTRS2005

Lunar Seismic Detector to Advance the Search for Strange Quark Matter

Detection of small seismic signals on the Moon are needed to study lunar internal structure and to detect possible signals from Strange Quark m&er transit events. The immediate objective is to create a prototype seismic detector using a tunnel diode oscillator with a variable capacitor attached to a proof mass. The device is designed to operate effectively on the Moon, which requires a low power consumption to operate through lunar night, while preserving sensitivity. The goal is capacitance resolution of better than 1 part in 10' and power consumption of less than 1 watt.

Galitzki, Nicholas B.↗