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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 1,639 records · Page 91

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NASA NTRS2023

Integrated Control Design for A Partially Turboelectric Aircraft Propulsion System

Electrified Aircraft Propulsion (EAP) holds great potential for reducing aviation emissions and fuel burn. A variety of EAP architectures have been proposed including partially-turboelectric configurations that combine turbofan engines with motor-driven propulsors. Such architectures exhibit coupling between subsystems and thus require an integrated control solution. To address this need, this paper presents an integrated control design strategy for a commercial single-aisle partially-turboelectric aircraft concept consisting of two wing-mounted turbofan engines and an electric motor driven tailfan propulsor. Within this architecture the turbofans serve the dual purpose of generating thrust and supplying mechanical offtake power used to generate electricity for the tailfan motor. The propulsion control system is tasked with coordinating turbofan and tailfan operation under both steady-state and transient scenarios. The paper introduces a linear state-space representation of the architecture reflecting the coupling between the turbofan and tailfan subsystems along with loop transfer functions reflecting open- and closed-loop system dynamics. Also discussed is an applied strategy for scheduling the tailfan setpoint command based on the average sensed fan speed of the two turbofans. This approach ensures synchronized operation of the turbofan and tailfan subsystems while also allowing the turbofan fuel control design to be simplified. Performance of the integrated control design is assessed through a real-time hardware-in-the-loop test conducted at the NASA Electric Aircraft Testbed. During this test a scaled version of the electrical system and turbomachinery shaft dynamics were implemented in electrical machine hardware and evaluated under closed-loop control. Results from this facility test are presented to illustrate the efficacy of the applied integrated control design approach under steady-state and transient scenarios including a full-flight mission profile.

Electrified Aircraft Propulsion↗

DOE OSTI2017

Xanthos

Xanthos is a Python package designed to quantify and analyze global water availability in history and in future at 0.5° × 0.5° spatial resolution and a monthly time step under a changing climate. Its performance was also tested through real applications. It is open-source, extendable and convenient to researchers who work on long-term climate data for studies of global water supply, and Global Change Assessment Model (GCAM). This package integrates inherent global gridded data maps, I/O modules, Water-Balance Model modules and diagnostics modules by user-defined configuration.

Source record↗

DOE OSTI2024

PV Generation and Load Forecasting for Adjuntas PR Community Microgrids

Existing frameworks to forecast time-series photovoltaic (PV) output power and consumer load for microgrid operations and controls assume a near-continuous availability of real-time input features from the field assets such as PV inverters, energy meters, and weather station. These incoming data points are used to periodically retrain models and update forecast snapshots over a moving horizon window, be it one hour-ahead, one-day ahead, or one-week ahead. However, such frameworks are not resilient to disruptions in data availability caused by losses in communications between the field sensors and data loggers. Hence, there is a need for programs that assume no availability of real-time microgrid asset data and still make reliable forecasts that can be used for decision-making. Such programs would be apt to function in extreme weather events such as hurricanes and would use lightweight recursive time-series models to independently forecast solar irradiance and ambient temperature, then compute PV power from those forecasts, as well as independently forecast consumer load. The codebase performs forecasting for the scenario of when the microgrid does not have a reliable access to forecasts or real-time observations of solar irradiance (I) and ambient temperature (AT) and load (Load) to be able to adequately forecast, in real-time, the PV power production or a business' load. In this case, using historical values of PV power and load, a univariate forecasting of generation and consumption are respectively made. The use-case in particular has two sub-scenarios: one, a normal 7-day ahead forecast where the unavailability of real-time data is assumed due to infrastructure issues such as loss of communication or sensor maintenance or service downtimes. Whereas a hurricane-caused unavailability of real-time data requires a second model trained specifically on historical hurricane days to be able to capture the extreme day behavior of generation in particular, and load if applicable. A gradient boosted regression tree comprises an ensemble of additive models that map between the input of historical values (be it irradiance, temperature, or load) and their corresponding output forecasts of a given horizon such that the individual learner predictions are summed up over the total number of such learners in the ensemble to produce an aggregate forecast. A weighting mechanism is applied to the training data in each iteration, where actual and forecast values are compared to penalize incorrect forecasts by increasing the weight and reducing it to reward correct forecasts. The code's benefits are that it: (a) accounts for a contingency where communication loss renders newly measured real-time data unavailable for model tuning and snapshot updates; (b) presents blind forecasting that recursively determines the next time-step value in a horizon using the forecast of the same attribute from a prior step; and (c) employs lightweight models that, once trained, can reliably generalize for different horizons, which make them suitable for enhancing the resilience of field microgrids prone to extreme events that encounter disruptions to data availability.

Sundararajan, Aditya [Oak Ridge National Laborator↗

NASA NTRS1994

Missileborne Artificial Vision System (MAVIS)

Several years ago when INTEL and China Lake designed the ETANN chip, analog VLSI appeared to be the only way to do high density neural computing. In the last five years, however, digital parallel processing chips capable of performing neural computation functions have evolved to the point of rough equality with analog chips in system level computational density. The Naval Air Warfare Center, China Lake, has developed a real time, hardware and software system designed to implement and evaluate biologically inspired retinal and cortical models. The hardware is based on the Adaptive Solutions Inc. massively parallel CNAPS system COHO boards. Each COHO board is a standard size 6U VME card featuring 256 fixed point, RISC processors running at 20 MHz in a SIMD configuration. Each COHO board has a companion board built to support a real time VSB interface to an imaging seeker, a NTSC camera, and to other COHO boards. The system is designed to have multiple SIMD machines each performing different corticomorphic functions. The system level software has been developed which allows a high level description of corticomorphic structures to be translated into the native microcode of the CNAPS chips. Corticomorphic structures are those neural structures with a form similar to that of the retina, the lateral geniculate nucleus, or the visual cortex. This real time hardware system is designed to be shrunk into a volume compatible with air launched tactical missiles. Initial versions of the software and hardware have been completed and are in the early stages of integration with a missile seeker.

Andes, David K.↗

NASA NTRS1990

An expert system to perform on-line controller restructuring for abrupt model changes

This paper presents the work in progress on an expert system utilized to tune and reconfigure airframe/engine control systems on-line in real time in response to structural or battle damage failures. The closed loop system is monitored constantly for changes in performance and structure, which detection prompts the expert system to select and apply a particular control restructuring algorithm based on the severity and type of damage. Control restructuring algorithms that have been implemented handle most failure cases involving actuator damage (control mixer) and many instances where the system dynamics are altered as well (modified control mixer).

Litt, Jonathan↗

NASA NTRS2014

Validation of TRMM Multi-Satellite Precipitation Analysis (TMPA) Products in the Peruvian Andes

The relevance of accurate and timely rainfall estimates cannot be overstated. The rainfall gauge network is still insufficient across significant areas worldwide. Rainfall estimates fromspaceborne sensors present an opportunity to supplement the existing network and enable the development of critical, near real time applications. However, the societal benefits of such systems can only be realized if the estimates are properly validated and the performance of existing products accurately described. In this study, two products generated by the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are validated for the Peruvian Andes. This is a region of complex topography that poses significant challenges to the retrieval of rainfall values fromspace. The TMPA products, both research grade (3B42V7) and near real time (3B42RT), are compared against in situ data. Different observation lengths are studied and the results are analyzed in light of geographic, topographic and climatic constraints. The Time Series of the science grade product were also studied under Dynamic TimeWarping and Hierarchical Clustering to streamline intertile comparisons. The TMPA products showa good agreementwith the gauge values, especially formore prolonged observation periods (over 8 days). The validation results display a strong regional dependence as a consequence of differences in the climate and topography. This region-specific performance calls for additional, detailed case studies and localized validation efforts. Overall the TMPAwas found to performadequately and provide quality information for a number of applications requiring timely estimates in convenient formats.

satellites↗

DOE OSTI2017

Real-Time Fine Grained Occupancy Estimation Using Depth Sensors on ARM Embedded Platforms

Occupancy estimation is an important primitive for a wide range of applications including building energy efficiency, safety, and security. In this paper, we explore the potential of using depth sensors to detect, estimate, identify, and track occupants in buildings. While depth sensors have been widely used for human detection and gesture recognition, computer vision algorithms are typically run on a powerful computer like XBOX or Intel R CoreTM i7 processor. In this work, we develop a prototype system called FORK using off-the-shelf components that performs the entire depth data processing on a cheaper and low power ARM processor in real-time. As ARM processors are extremely weak in running computer vision algorithms, FORK is designed to detect humans and track them in a very efficient way by leveraging a novel lightweight model based approach instead of traditional approaches based on histogram of oriented gradients (HOG) features. Unlike other camera based approaches, FORK is much less privacy invasive (even if the sensor is compromised). Based on a complete implementation, real-world deployment, and extensive evaluation at realistic scenarios, we observe that FORK achieves over 99% accuracy in real-time (4-9 FPS) in occupancy estimation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Enhanced Bottom Anode Monitoring in DC Electric Arc Furnaces Using Fiber-Optic Sensors

A pin style bottom anode employs conductive steel rods that serve as the pathway for the high electrical power through rammed refractory at the bottom of a DC Electric Arc Furnace (EAF). Anode wear during operation is important to monitor, as anode replacement is expensive and impacts EAF productivity. Liquid steel penetration into the un-sintered refractory layer can result from rapid electrical power ramp-up, dips in furnace temperature, or operating the anode for too long between EAF campaigns. In extreme cases, the liquid steel may penetrate the bottom of the furnace when anode wear progresses too close to the bottom shell, which is extremely dangerous and must be avoided. The current state of the art for monitoring bottom anode wear employs thermocouples imbedded in the anode pins at points in the anode. However, this approach is not sensitive enough to detect localized damage to the anode, especially when cracking occurs. Here, the present work utilizes fiber optic sensors to monitor the health of the anode, by creating a real-time spatially distributed temperature map of the anode. Unlike the traditional thermocouples, these sensors can be mounted at significantly greater depths, provide distributed temperature measurements, and can withstand temperatures of up to 900°C. Additionally, they are able to perform temperature measurements with a spatial resolution of 1.3 mm at a 5 Hz acquisition rate, providing unprecedented high-density real time monitoring of anode health and increasing the efficiency, and safety of EAF operation.

Bottom Anode↗

DOE OSTI2019

City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts

Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. The results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1996

High Stability Engine Control (HISTEC)

Future aircraft turbine engines, both commercial and military, must be able to successfully accommodate expected increased levels of steady-state and dynamic engine-face distortion. The current approach of incorporating a sufficient component design stall margin to tolerate these increased levels of distortion would significantly reduce performance. The objective of the High Stability Engine Control (HISTEC) program is to design, develop, and flight demonstrate an advanced, high-stability, integrated engine control system that uses measurement-based, real-time estimates of distortion to enhance engine stability. The resulting distortion tolerant control reduces the required design stall margin, with a corresponding increase in performance and decrease in fuel burn. The HISTEC concept, consisting of a Distortion Estimation System and a Stability Management Control, has been designed and developed. The Distortion Estimation System uses a small number of high-response pressure sensors at the engine face to calculate indicators of the type and extent of distortion in real time. The Stability Management Control, through direct control of the fan and compressor pressure ratio, accommodates the distortion by transiently increasing the amount of stall margin available based on information from the Distortion Estimation System. Simulation studies have shown the HISTEC distortion tolerant control is able to successfully estimate and accommodate time-varying distortion. Currently, hardware and software systems necessary for flight demonstration of the HISTEC concept are being designed and developed. The HISTEC concept will be flight tested in early 1997.

DeLaat, John C.↗

DOE OSTI2019

Evaluation of a Material Balance Only and Material Balance with Real-Time In-line Monitoring Approaches for DFLAW Processing

The Assistant Manager, WTP chartered an Integrated Technical Team (ITT), which includes personnel from the Savannah River National Laboratory (SRNL), Pacific Northwest National Laboratory (PNNL), from the Savannah River National Laboratory (SRNL), Pacific Northwest National Laboratory (PNNL), Bechtel National, Inc., and DOE-ORP, to evaluate the capability and potential benefits of replacing sample collection/analyses requirements with real-time, in-line monitoring. The initial focus of the ITT is the Direct Feed Low Activity Waste (DFLAW) Program. This work scope is being performed in multiple phases. The Phase 2 work scope contains tasks to evaluate a materials balance only approach as well as continuing scoping evaluations for instruments that could be used for Real-Time In-Line Monitoring (RTIM). The Phase 2 work scope for evaluation of a materials balance approach was completed by both SRNL and PNNL and is documented in this report. The material balance evaluation included a review of the WTP Low Activity Waste (LAW) vitrification process as well as the WTP Effluent Management Facility (EMF) process. Sampling requirements and unit operations were reviewed to determine which sample requirements could be met with a material balance without significantly increasing processing or reporting uncertainties.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Experimental setup combining in situ hard X-ray photoelectron spectroscopy and real-time surface X-ray diffraction for characterizing atomic and electronic structure evolution during complex oxide heterostructure growth

We describe the next-generation system for in situ characterization of a complex oxide thin film and heterostructure growth by pulsed laser deposition (PLD) using synchrotron hard X-rays. The system consists of a PLD chamber mounted on a diffractometer allowing both real-time surface X-ray diffraction (SXRD) and in situ hard X-ray photoelectron spectroscopy (HAXPES). HAXPES is performed in the incident X-ray energy range from 4 to 12 keV using a Scienta EW4000 electron energy analyzer mounted on the PLD chamber fixed parallel with the surface normal. In addition to the standard application mode of HAXPES for disentangling surface from bulk properties, the increased penetration depth of high energy photoelectrons is used for investigation of the electronic structure changes through thin films grown deliberately as variable thickness capping layers. Such heterostructures represent model systems for investigating a variety of critical thickness and dead layer phenomena observed at complex oxide interfaces. In this new mode of operation, in situ HAXPES is used to determine the electronic structure associated with unique structural features identified by real-time SXRD during thin film growth. The system is configured for using both laboratory excitation sources off-line and on-line operation at beamline 33-ID-D at the Advanced Photon Source. We illustrate the performance of the system by preliminary scattering and spectroscopic data on oxygen vacancy ordering induced perovskite-to-brownmillerite reversible phase transformation in La 2/3 Sr 1/3 MnO 3 films capped with oxygen deficient SrTiO 3–δ (100) layers of varying thickness.

47 OTHER INSTRUMENTATION↗

DOE OSTI2017

Substrate-Coated Illumination Droplet Spray Ionization: Real-Time Monitoring of Photocatalytic Reactions

Real-time monitoring of photocatalytic reactions facilitates the elucidation of the mechanisms of the reactions. However, suitable tools for real-time monitoring are lacking. Herein, a novel method based on droplet spray ionization named substrate-coated illumination droplet spray ionization (SCI-DSI) for direct analysis of photocatalytic reaction solution is reported. SCI-DSI addresses many of the analytical limitations of electrospray ionization (ESI) for analysis of photocatalytic-reaction intermediates, and has potential for both in situ analysis and real-time monitoring of photocatalytic reactions. In SCI-DSI-mass spectrometry (MS), a photocatalytic reaction occurs by loading sample solutions onto the substrate-coated cover slip and by applying UV light above the modified slip; one corner of this slip adjacent to the inlet of a mass spectrometer is the high-electric-field location for launching a charged-droplet spray. After both testing and optimizing the performance of SCI-DSI, the value of this method for in situ analysis and real-time monitoring of photocatalytic reactions was demonstrated by the removal of cyclophosphamide (CP) in TiO{sub 2}/UV. Reaction times ranged from seconds to minutes, and the proposed reaction intermediates were captured and identified by tandem mass spectrometry. Moreover, the free hydroxyl radical (·OH) was identified as the main radicals for CP removal. These results show that SCI-DSI is suitable for in situ analysis and real-time monitoring of CP removal under TiO{sub 2}-based photocatalytic reactions. SCI-DSI is also a potential tool for in situ analysis and real-time assessment of the roles of radicals during CP removal under TiO{sub 2}-based photocatalytic reactions.Graphical Abstract .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2020

Characterization of How CO2 Level May Impact Crew Performance Related to the HSIA Risk

Safety and mission critical anomalies are inevitable on NASA exploration missions. Delays and interruptions in communication with Earth-experts drives the requirement that crew resolve these anomalies on their own. The Human Factors and Behavioral Performance (HFBP) element of the NASA Human Research Program (HRP) recently stood-up the Human-System Integration Architecture (HSIA) risk. The specific risk statement is: “Given decreasing real-time ground support for execution of complex operations during future exploration missions, there is a possibility of adverse performance outcomes including that crew are unable to adequately respond to unanticipated critical malfunctions or detect safety critical procedural errors.” Reliable, on-board capabilities will need to support the crew - not only to resolve anomalies, but also to promote situation awareness (SA) and to reduce workload. Unfortunately, the present level of technological advancement limits the range of achievable intelligent support (Wu & Vera, 2019). The Human Capabilities Assessment for Autonomous Missions (HCAAM) projects were devised to identify how technology may benefit crew situation awareness and enhance crew trust in the intelligent systems. A suite of time-critical and complex exploration tasks have been identified (Holden et al., 2019) that may advance human-integration Concept of Operations (ConOps) development. This ConOps (a future HFBP directed task) along with standards and guidelines (Holden et al., 2019) may be used as the foundation for human-system requirements for a self-reliant crew. Spaceflight CO2 levels are elevated relative to terrestrial levels. Above 2.5 mmHg there is an increase in the incidence of crew headaches (Law et al., 2014) and Mission Control reports of mood and performance changes in the crew. The concern is that elevated CO2 effects may exacerbate the HSIA risk. Unfortunately, effects of higher concentrations of CO2 on performance decrements are not well established. The main goal of the current report is to identify how elevated CO2 impacts the HSIA risk. The approach taken is to trace the relationship between cognitive and motor abilities required for anomaly response with critical mission tasks and the level of technological advancement to support anomaly resolution to identify how elevated CO2 may impact the HSIA risk. The conclusion is that elevated CO2 could exacerbate the HSIA risk. Several research gaps are identified.

cognition↗

DOE OSTI2022

LHC physics dataset for unsupervised New Physics detection at 40 MHz

In the particle detectors at the Large Hadron Collider, hundreds of millions of proton-proton collisions are produced every second. If one could store the whole data stream produced in these collisions, tens of terabytes of data would be written to disk every second. The general-purpose experiments ATLAS and CMS reduce this overwhelming data volume to a sustainable level, by deciding in real-time whether each collision event should be kept for further analysis or be discarded. We introduce a dataset of proton collision events that emulates a typical data stream collected by such a real-time processing system, pre-filtered by requiring the presence of at least one electron or muon. This dataset could be used to develop novel event selection strategies and assess their sensitivity to new phenomena. In particular, we intend to stimulate a community-based effort towards the design of novel algorithms for performing unsupervised new physics detection, customized to fit the bandwidth, latency and computational resource constraints of the real-time event selection system of a typical particle detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Anomaly Detection Based on Machine Learning for the CMS Electromagnetic Calorimeter Online Data Quality Monitoring

Using a semi-supervised machine learning approach we present a real-time anomaly detection system based on an autoencoder used for online data quality monitoring of the CMS electromagnetic calorimeter operating at the CERN LHC. We introduce a novel method that maximizes the anomaly detection performance making use of the time-dependence of anomalies and the spatial variations in the detector response. The autoencoder-based system efficiently detects anomalies in real time and maintains a very low false discovery rate. We validate the performance of this novel system with anomalies from LHC collision data taken in 2018 and 2022. In addition, results are presented after deploying the autoencoder-based system in the CMS online Data Quality Monitoring workflow at the beginning of LHC Run 3 resulting in the system to detect issues that were missed by the existing system.

Harilal, Abhirami [Carnegie Mellon University, Pit↗

NASA NTRS1982

A Piecewise Linear State Variable Technique for Real Time Propulsion System Simulation

The emphasis on increased aircraft and propulsion control system integration and piloted simulation has created a need for higher fidelity real time dynamic propulsion models. A real time propulsion system modeling technique which satisfies this need and which provides the capabilities needed to evaluate propulsion system performance and aircraft system interaction on manned flight simulators was developed and demonstrated using flight simulator facilities at NASA Ames. A piecewise linear state variable technique is used. This technique provides the system accuracy, stability and transient response required for integrated aircraft and propulsion control system studies. The real time dynamic model includes the detail and flexibility required for the evaluation of critical control parameters and propulsion component limits over a limited flight envelope. The model contains approximately 7.0 K bytes of in-line computational code and 14.7 K of block data. It has an 8.9 ms cycle time on a Xerox Sigma 9 computer. A Pegasus-Harrier propulsion system was used as a baseline for developing the mathematical modeling and simulation technique. A hydromechanical and water injection control system was also simulated. The model was programmed for interfacing with a Harrier aircraft simulation at NASA Ames. Descriptions of the real time methodology and model capabilities are presented.

Mihaloew, J. R.↗

NASA NTRS1982

A piecewise linear state variable technique for real time propulsion system simulation

Mihaloew, J. R.↗