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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Use of the updated NASA Langley radio-controlled drop-model technique for high-alpha studies of the X-29A configuration

This paper presents an overview of the radio-controlled drop-model technique used for low-speed flight dynamics research at the NASA Langley Research Center. The overall test methodology is reviewed and the major elements of the system are discussed including model construction and equipment, the closed-loop control system, and the flight test facility. To illustrate the capabilities of the technique, selected results from an ongoing program to study the high-angle-of-attack flight dynamics of the X-29A configuration are reviewed. Three research areas are highlighted: motion prediction, control system effects, and motion analysis and modeling. Finally, several current upgrades to the overall technique are discussed along with the enhanced test capability that they will provide.

Fratello, David J.↗
NASA NTRS2004

GVE-Based Dynamics and Control for Formation Flying Spacecraft

Formation flying is an enabling technology for many future space missions. This paper presents extensions to the equations of relative motion expressed in Keplerian orbital elements, including new initialization techniques for general formation configurations. A new linear time-varying form of the equations of relative motion is developed from Gauss Variational Equations and used in a model predictive controller. The linearizing assumptions for these equations are shown to be consistent with typical formation flying scenarios. Several linear, convex initialization techniques are presented, as well as a general, decentralized method for coordinating a tetrahedral formation using differential orbital elements. Control methods are validated using a commercial numerical propagator.

Breger, Louis↗
DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Dual blockade of IL-10 and PD-1 leads to control of SIV viral rebound following analytical treatment interruption

Human immunodeficiency virus (HIV) persistence during antiretroviral therapy (ART) is associated with heightened plasma interleukin-10 (IL-10) levels and PD-1 expression. We hypothesized that IL-10 and PD-1 blockade would lead to control of viral rebound following analytical treatment interruption (ATI). Twenty-eight ART-treated, simian immunodeficiency virus (SIV)mac 239 -infected rhesus macaques (RMs) were treated with anti-IL-10, anti-IL-10 plus anti-PD-1 (combo) or vehicle. ART was interrupted 12 weeks after introduction of immunotherapy. Durable control of viral rebound was observed in nine out of ten combo-treated RMs for >24 weeks post-ATI. Induction of inflammatory cytokines, proliferation of effector CD8 + T cells in lymph nodes and reduced expression of BCL-2 in CD4 + T cells pre-ATI predicted control of viral rebound. Twenty-four weeks post-ATI, lower viral load was associated with higher frequencies of memory T cells expressing TCF-1 and of SIV-specific CD4 + and CD8 + T cells in blood and lymph nodes of combo-treated RMs. These results map a path to achieve long-lasting control of HIV and/or SIV following discontinuation of ART.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Enhancing SRF cavity stability and minimizing detuning with data-driven resonance control based on dynamic mode decomposition

Effective resonance control of superconducting radio frequency (SRF) cavities is critical for large machines like LCLS-II, as failure to achieve proper control can result in increased RF power consumption, higher cryogenic heat loads, and increased costs. To address this challenge, we have developed a machine learning (ML) model based on the dynamic mode decomposition method to represent the forced cavity dynamics. Using this model, we designed a model predictive controller (MPC) and demonstrated through simulation that the MPC can effectively stabilize the amplitude and phase of SRF cavities using only a frequency actuator, even in the presence of multiple mechanical modes. The lightweight and explicit ML model makes the controller suitable for direct implementation on field-programmable gate arrays, unlocking the full potential of SRF linacs like LCLS-II, enabling higher beam power and energy, and also serving as an advanced motion controller for various applications, such as photon beamlines and storage rings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2011

Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler (Final Technical Report)

This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC fouling). In parallel, an MPC solution was initially developed using ideal sensing to optimize the plant operation during startup pre-heating as well as steady state and transient operation under normal high-pressure conditions, e.g. part-load, base-load, load transition and fuel changes. The MPC simulation studies showed significant improvements both for startup pre-heating and for normal operation. Finally, the EKF and MPC solutions were coupled to achieve the integrated sensing and control solution and its performance was studied through extensive steady state and transient simulations in the presence of sensor and modeling errors. The results of each task in the program and overall conclusions are summarized in this final report.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Performance Evaluation of Gray-box and Machine Learning Models of a Thermal Energy Storage System with Active Insulation

An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.

Cui, Borui↗
DOE OSTI2024

Building Automation

In this chapter, we focus on both need-based and vision-based control innovation for building automation for HVAC systems. After providing a brief background that describes different HVAC architectures and products, we describe the control challenges and opportunities from a needs-based point of view, at the equipment level, the systems level, and the building level. At the equipment level, increased use of continuously variable actuation such as variable speed compressors and fans, requires application of robust multivariable control that must consider various types of nonlinear behavior across increasingly larger operating envelopes. The objective at this level is to achieve robust and energy efficient operation. At the system level, coupled and interactive dynamics among subsystems are increasingly important to consider, and functional integration of these subsystems, along with set points and operating schedules are designed to minimize energy consumption and improve occupant comfort. At the building level, issues such as integration among other building systems, such as the building envelope and the electric grid, offer opportunities to develop new types of demand response and grid-interactive behaviors and technologies. At the higher levels, system dynamics and robust stability are less of an issue, similar to process control applications, while optimization and integration are more important, although dynamic stability is increasing an issue at the higher levels too. From a vision-driven innovation point of view, we describe three areas that will require sustained research efforts and will eventually impact building automation: Digital Twins, Model Predictive Control, and Grid Interactive Buildings.

Bortoff, Scott↗
DOE OSTI2024

Development of Supervisory Control System for Thermal Energy Distribution System

The integrated energy system (IES) refers to the combination of nuclear energy generation with other energy sources to enable the efficiency and reliability of power generations. To create technologically viable and economically competitive systems, supervisory control strategies are critical for optimizing performance and ensuring stability across different energy generation, transportation, and utilization. This work focuses on the control strategies for the thermal energy distribution system (TEDS), which is a cornerstone of the Dynamic Energy Transport and Integration Laboratory at Idaho National Laboratory. TEDS currently relies on operators to coordinate across different components to manage energy storage and ensure efficiency. This work demonstrates the use of model predictive control (MPC) with surrogate models in determining optimal setpoints for major TEDS components. The capability of MPC-based supervisory control system is evaluated by autonomously matching the power outputs from a Dymola-based TEDS with target heat demands.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2014

Safe Maritime Autonomous Path Planning in a High Sea State

This paper presents a path planning method for sea surface vehicles that prevents capsizing and bow-diving in a high sea-state. A key idea is to use response amplitude operators (RAOs) or, in control terminology, the transfer functions from a sea state to a vessel's motion, in order to find a set of speeds and headings that results in excessive pitch and roll oscillations. This information is translated to arithmetic constraints on the ship's velocity, which are passed to a model predictive control (MPC)-based path planner to find a safe and optimal path that achieves specified goals. An obstacle avoidance capability is also added to the path planner. The proposed method is demonstrated by simulations.

Ono, Masahiro↗
DOE OSTI2012

Pretreatment Endorectal Coil Magnetic Resonance Imaging Findings Predict Biochemical Tumor Control in Prostate Cancer Patients Treated With Combination Brachytherapy and External-Beam Radiotherapy

Purpose: To investigate the utility of endorectal coil magenetic resonance imaging (eMRI) in predicting biochemical relapse in prostate cancer patients treated with combination brachytherapy and external-beam radiotherapy. Methods and Materials: Between 2000 and 2008, 279 men with intermediate- or high-risk prostate cancer underwent eMRI of their prostate before receiving brachytherapy and supplemental intensity-modulated radiotherapy. Endorectal coil MRI was performed before treatment and retrospectively reviewed by two radiologists experienced in genitourinary MRI. Image-based variables, including tumor diameter, location, number of sextants involved, and the presence of extracapsular extension (ECE), were incorporated with other established clinical variables to predict biochemical control outcomes. The median follow-up was 49 months (range, 1-13 years). Results: The 5-year biochemical relapse-free survival for the cohort was 92%. Clinical findings predicting recurrence on univariate analysis included Gleason score (hazard ratio [HR] 3.6, p = 0.001), PSA (HR 1.04, p = 0.005), and National Comprehensive Cancer Network risk group (HR 4.1, p = 0.002). Clinical T stage and the use of androgen deprivation therapy were not correlated with biochemical failure. Imaging findings on univariate analysis associated with relapse included ECE on MRI (HR 3.79, p = 0.003), tumor size (HR 2.58, p = 0.04), and T stage (HR 1.71, p = 0.004). On multivariate analysis incorporating both clinical and imaging findings, only ECE on MRI and Gleason score were independent predictors of recurrence. Conclusions: Pretreatment eMRI findings predict for biochemical recurrence in intermediate- and high-risk prostate cancer patients treated with combination brachytherapy and external-beam radiotherapy. Gleason score and the presence of ECE on MRI were the only significant predictors of biochemical relapse in this group of patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

New nutrients exert fundamental control on dissolved organic carbon accumulation in the surface Atlantic Ocean

The inventories of carbon residing in organic matter dissolved in the ocean [dissolved organic carbon (DOC)] and in the atmosphere as CO 2 are of the same order of magnitude, such that small changes in the DOC pool could have important consequences in atmospheric carbon and thus climate. DOC in the global ocean is largely formed in the sunlit euphotic zone, but identifying predictable controls on that production is an important yet unrealized goal. In this paper, we use a testable and causative correlation between the net production of DOC and the consumption of new nutrients in the euphotic zone of the Atlantic Ocean. We demonstrate that new nutrients introduced to the euphotic zone by upwelling in divergence zones and by winter convective overturn of the water column, and the primary production associated with those nutrients, are the ultimate driver of DOC distributions across the Atlantic basins. Finally, as new nutrient input will change with a changing climate, the role of DOC in the ocean’s biological pump should likewise be impacted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Beyond the Active Site: The Impact of the Outer Coordination Sphere on Electrocatalysts for Hydrogen Production and Oxidation

Hydrogenase enzymes provide inspiration for investigations of molecular catalysts utilizing structural and functional mimics of the active site. However, the resulting active site mimics cannot match the combination of high rates and low overpotentials of the enzyme, suggesting that the rest of the protein scaffold, i.e., the outer coordination sphere, is necessary for the efficiency of hydrogenase. Therefore, inclusion of outer coordination sphere elements onto molecular catalysts may enable us to achieve and ultimately surpass the overall enzymatic efficiency. In an effort to identify and include the missing enzymatic features, there has been recent effort to understand the effect of outer coordination sphere elements on molecular catalysts for hydrogen oxidation and production. Our focus has been to utilize amino acid or peptide based scaffolds on an active functional mimic for hydrogen oxidation and production, [Ni(PR2NR’2)2]2+. This bottom-up approach, i.e, building an outer coordination sphere around a functional molecular catalyst, has allowed us to evaluate individual contributions to catalysis, including enhancing proton movement, concentrating substrate and introducing structural features to control reactivity. Collectively, these studies have resulted in catalysts that can operate faster, can operate at lower overpotentials, have enhanced water solubility, and/or can provide more stability to oxygen or extreme conditions such as strongly acidic or basic conditions than their unmodified parent complexes. Common mechanisms have yet to be defined to predictably control these processes but our growing knowledge in this area is essential for the eventual mimicry of enzymes for developing efficient molecular catalysts for practical use. This account reviews previously published work supported by the US DOE Basic Energy Sciences (BES), Physical Bioscience program, the Office of Science Early Career Research Program through the USDOE, BES, the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the US DOE, Office of Science, Office of BES. Part of the research was conducted at the W.R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by U.S. DOE’s Office of Biological and Environmental Research program located at Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for the U.S. Department of Energy.

bioinspired↗
DOE OSTI2016

Experimental Demonstration of Frequency Regulation by Commercial Buildings – Part II: Results and Performance Evaluation

This paper is the second part of a two-part series presenting the results from an experimental demonstration of frequency regulation in a commercial building test facility. We developed relevant building models and designed a hierarchical controller for reserve scheduling, building climate control and frequency regulation in Part I. In Part II, we introduce the communication architecture and experiment settings, and present extensive experimental results under frequency regulation. More specifically, we compute the day-ahead reserve capacity of the test facility under different assumptions and conditions. Furthermore, we demonstrate the ability of model predictive control to satisfy comfort constraints under frequency regulation, and show that fan speed control can track the fast-moving RegD signal of the Pennsylvania, Jersey, and Maryland Power Market (PJM) very accurately. In addition, we discuss potential effects of frequency regulation on building operation (e.g., increase in energy consumption, oscillations in supply air temperature, and effect on chiller cycling), and provide suggestions for real-world implementation projects. Lastly, our results show that hierarchical control is appropriate for frequency regulation from commercial buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Offline Arterial Signal Timing Optimization for Closely Spaced Intersections

The stop-and-go driving behavior at a busy arterial causes a significant amount of fuel waste and emissions that could be reduced. For closely spaced intersections, the traditional bottom-up signal timing approach could fail under high volumes when the queues reach the upstream intersections. A well-coordinated arterial should manage the queue length to prevent the control from failing. Traditionally, coordination among signalized intersections for an arterial means finding the good offsets for each intersection. The control of the intersections along an arterial can also be coordinated by optimizing splits. Splits impact the capacity of an intersection. Similar to the highway, the capacity drop could cause growing queues. This work is based on the Virtual Phase-Link (VPL) model, a street traffic model designed for online traffic model predictive control, to obtain a top-down offline arterial signal timing. The VPL-based model can guarantee capacity consistency in intersections along an arterial. We, therefore, adopted the VPL-based model and developed an offline signal timing optimization approach. The proposed timing derived from the VPL-based offline signal timing optimization showed very good results in simulation. We also collected field experiment data, which demonstrated overall energy reductions and speed improvements on some sections of the study arterial.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Real-Time Ecodriving Control in Electrified Connected and Autonomous Vehicles Using Approximate Dynamic Programing

Connected and automated vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the ecodriving problem seeks to design optimal speed and power usage profiles based on available information from connectivity and advanced mapping features to minimize the fuel consumption over an itinerary. This paper presents a hierarchical multilayer model predictive control (MPC) approach for improving the fuel economy of a 48 V mild-hybrid powertrain in a connected vehicle environment. Approximate dynamic programing (DP) is used to solve the receding horizon optimal control problem, whose terminal cost is approximated with the base policy obtained from the long-term optimization. The controller was tested virtually (with deterministic and Monte Carlo simulation) across multiple real-world routes, demonstrating energy savings of more than 20%. The controller was then deployed on a test vehicle equipped with a rapid prototyping embedded controller. In-vehicle testing confirm the energy savings obtained in simulation and demonstrate the real-time ability of the controller.

Automation & Control Systems↗
DOE OSTI2023

Incorporating Operational Uncertainties into the Dispatch of an Integrated Solar and Storage System

The economic assessment of hybrid energy systems (HES) pairing battery energy storage systems (BESSs) and photovoltaics (PV) is highly important for advancing their deployment in power systems. This paper presents an innovative assessment framework, including an optimal control policy for dispatch under uncertainty and procedures for exploring control parameters that maximize economic benefits. The proposed dispatch policy consists of two steps using system forecast information. The first step is to determine whether a BESS will be used within an operational scheduling time frame based on the probability of events and their thresholds. Once the dispatch of BESS is triggered, a model predictive control (MPC) is carried out in the second step for scheduling using the expected value of system information. By exercising this policy with different thresholds, one can explore the trade-offs between short-term benefits and battery lifetime, and identify an optimal threshold that maximizes the total economic benefits within the battery lifetime. An evaluation study in a real-world HES project is presented to illustrate the proposed framework. Compared with traditional optimal dispatch algorithms, the proposed method can significantly improve the economic benefits of an HES scheduled under forecast uncertainties.

Ma, Xu↗