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At least 235 records · Page 13

Loads Due to Controls at Transonic and Low Supersonic Speeds

Some results of recent experimental investigations at supersonic and transonic speeds are presented to show the present status in the estimation of load distributions on controls and adjacent wing surfaces resulting from the deflection of flap controls and spoiler controls. The results indicate that the development of methods for predicting loads associated with controls has not kept pace with the acquisition of experimental data. At low supersonic speeds sweeping the hinge line induces strong three-dimensional-flow characteristics which cannot be treated by the simplified methods previously developed for controls without sweep. At transonic speeds the estimation of loads associated with controls must usually be dependent upon experimental information inasmuch as the latest attempts to predict chordwise and spanwise loadings have met with only limited success.

West, F. E, Jr↗

Distribution of SLS Integrated Load Uncertainty to Surface Pressures and Sectional Loads

Aerodynamic loads that are important to launch vehicle programs such as NASA’s Space Launch System (SLS) include both integrated loads such as the force & moment on the entire vehicle and distributed loads. In this work two examples of distributed loads are considered: the pressure field on the surface of the vehicle and sectional loads, which are one-dimensional distributions along the axis of the launch vehicle. In some modern flight programs, the integrated loads, such as lift and drag, used to design the guidance and control laws for the vehicle come from wind tunnel testing, while distributed loads are produced using Computational Fluid Dynamics(CFD). The first task that is addressed in this paper, then, is to provide a formal method to adjust the distributed loads so that integrating them matches the prescribed integrated load. In addition, the integrated loads in a launch vehicle typically include an uncertainty estimate. The second task is to distribute this prescribed integrated uncertainty to each point in a distributed load. Both tasks are addressed using the same technique, which is to create distributed load profiles that isolate adjustments to one integrated load while leaving the others unaffected. These adjustments are informed by Proper Orthogonal Decomposition (POD) of the entire CFD-based distributed load database. Once applied, the adjusted distributed loads can be used to evaluate any scalar quantity of interest that might be needed by downstream users such as structural analysis or trajectory modelers.

SLS↗

Pressure Distribution over a Wing and Tail Rib of a VE-7 and of a TS Airplane in Flight

This investigation was made to determine the pressure distribution over a rib of the wing and over a rib of the horizontal tail surface of an airplane in flight and to obtain information as to the time correlation of the loads occurring on these ribs. Two airplanes, VE-7 and TS, were selected in order to obtain the information for a thin and a thick wing section. In each case the pressure distribution was recorded for the full range of angle of attack in level flight and throughout violent maneuvers. The results show: (a) that the present rib load specifications in use by the Army Air Corps and the Bureau of Aeronautics, Navy Department, are in fair agreement with the loads actually occurring in flight, but could be slightly improved; (b) that there appears to be no definite sequence in which wing and tail surface ribs reach their respective maximum loads in different maneuvers; (c) that in accelerated flight, at air speeds less than or equal to 60 per cent of the maximum speed, the accelerations measured agree very closely with the theoretically possible maximum accelerations. In maneuvers at higher air speeds the observed accelerations were smaller than those theoretically possible. (author)

Crowley, J W , Jr↗

Supervisory On-line Optimal Control of an Electric Power Microgrid Design for Lunar Habitation

The following article describes an optimal control algorithm for the operation and study of an electric microgrid designed to power a lunar habitat. A photovoltaic (PV) generator powers the habitat and the presence of predictable lunar eclipses necessitates a system to prioritize and control loads within the microgrid. The algorithm consists of a reduced order model (ROM) that describes the microgrid, a discretization of the equations that result from the ROM, and an optimization formulation that controls the microgrid’s behavior. In order to validate this approach, the paper presents results from simulation based on lunar eclipse information and a schedule of intended loads.

Joseph Young↗

Comprehensive Material Characterization and Simultaneous Model Calibration for Improved Computational Simulation Credibility

Computational simulation is increasingly relied upon for high-consequence engineering decisions, and a foundational element to solid mechanics simulations is a credible material model. Our ultimate vision is to interlace material characterization and model calibration in a real-time feedback loop, where the current model calibration results will drive the experiment to load regimes that add the most useful information to reduce parameter uncertainty. The current work investigated one key step to this Interlaced Characterization and Calibration (ICC) paradigm, using a finite load-path tree to incorporate history/path dependency of nonlinear material models into a network of surrogate models that replace computationally-expensive finite-element analyses. Our reference simulation was an elastoplastic material point subject to biaxial deformation with a Hill anisotropic yield criterion. Training data was generated using either a space-filling or adaptive sampling method, and surrogates were built using either Gaussian process or polynomial chaos expansion methods. Surrogate error was evaluated to be on the order of 10 ⁻5 and 10 ⁻3 percent for the space-filling and adaptive sampling training data, respectively. Direct Bayesian inference was performed with the surrogate network and with the reference material point simulator, and results agreed to within 3 significant figures for the mean parameter values, with a reduction in computational cost over 5 orders of magnitude. These results bought down risk regarding the surrogate network and facilitated a successful FY22-24 full LDRD proposal to research and develop the complete ICC paradigm.

36 MATERIALS SCIENCE↗

Estimating turbine limit load

A method for estimating turbine limit-load pressure ratio from turbine map information is presented and demonstrated. It is based on a mean line analysis at the last-rotor exit. The required map information includes choke flow rate at all speeds as well as pressure ratio and efficiency at the onset of choke at design speed. One- and two-stage turbines are analyzed to compare the results with those from a more rigorous off-design flow analysis and to show the sensitivities of the computed limit-load pressure ratios to changes in the key assumptions.

Glassman, Arthur J.↗

Decentralized Low-Rank State Estimation for Power Distribution Systems

This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗

Microgravity Investigation of Crew Reactions in 0-G (MICR0-G): Ground-Based Development Effort

This report describes the technology development of an advanced load sensor ground-based prototype and details the preliminary tests in microgravity during parabolic flights. The research effort is entitled, the Microgravity Investigation and Crew Reactions in 0-G (MICR0-G), a ground-based research effort funded by the National Aeronautics and Space Administration (NASA). The MICR0-G project was a follow-on to the Enhanced Dynamic Load Sensors (EDLS) spaceflight experiment flown on the Russian Space Station Mir. The technology development of the advanced load sensor prototype has been carried out by the Massachusetts Institute of Technology (MIT), with collaboration from Politecnico di Milano University and the Italian Space Agency (ASI). The key hardware of the advanced sensor prototype is a set of two types of load sensors - a hand-hold and foot restraints - similar in appearance to the mobility aids found in the Space Shuttle orbiter to assist the crew in moving inside the spacecraft, but able to measure the applied forces and moments about the x-, y-, and z- axes. The aim of Chapter 1 is to give a brief overview of the report contents. The first section summarizes the previous research efforts on astronaut-induced loads in microgravity. The second section provides information on the MICR0-G research project and the technology development work conducted at MIT. Section 1.3 details the motivation for designing a new generation of load sensors and describes the main enhancements and contributions of the MICR0-G advanced load sensors system compared to the EDLS system. Finally, the last section presents the outline of the report.

Newman, Dava J.↗

Analysis of the 60-Hz power system at KSC: The Orsino substation

An analysis of the Orsino Substation, a component (50 percent) of the 60-Hertz electric power system at the Kennedy Space Center, is presented. Presented here are separate single-line diagrams of the sixteen feeder circuits to permit easy access to information on the individual feeders for future planning. The load condition of each feeder and load break switch are presented and a heuristic reliability analysis of the system is performed. Information is given about the system fashion useful for decision making purposes. The beauty of it is in the simplified manner by which information about the system can be obtained.

Kalu, Alex O.↗

Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System

The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

K-anonymity applied to the energy grid of things distributed energy resource management system

Smart grid infrastructure relies on information exchange between multiple actors in order to ensure system reliability. These actors include but are not limited to smart loads, grid control, and energy management technologies. As information exchange between these actors is susceptible to cyber-attacks, security and privacy issues are indispensable to ensure a reliable and stable grid. This position paper proposes a privacypreserving, trust-augmented secure scheme for a smart grid implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Atmospheric Environments for Entry, Descent and Landing (EDL)

Scientific measurements of atmospheric properties have been made by a wide variety of planetary flyby missions, orbiters, and landers. Although landers can make in-situ observations of near-surface atmospheric conditions (and can collect atmospheric data during their entry phase), the vast majority of data on planetary atmospheres has been collected by remote sensing techniques from flyby and orbiter spacecraft (and to some extent by Earth-based remote sensing). Many of these remote sensing observations (made over a variety of spectral ranges), consist of vertical profiles of atmospheric temperature as a function of atmospheric pressure level. While these measurements are of great interest to atmospheric scientists and modelers of planetary atmospheres, the primary interest for engineers designing entry descent and landing (EDL) systems is information about atmospheric density as a function of geometric altitude. Fortunately, as described in in this paper, it is possible to use a combination of the gas-law relation and the hydrostatic balance relation to convert temperature-versus-pressure, scientific observations into density-versus-altitude data for use in engineering applications. The following section provides a brief introduction to atmospheric thermodynamics, as well as constituents, and winds for EDL. It also gives methodology for using atmospheric information to do "back-of-the-envelope" calculations of various EDL aeroheating parameters, including peak deceleration rate ("g-load"), peak convective heat rate. and total heat load on EDL spacecraft thermal protection systems. Brief information is also provided about atmospheric variations and perturbations for EDL guidance and control issues, and atmospheric issues for EDL parachute systems. Subsequent sections give details of the atmospheric environments for five destinations for possible EDL missions: Venus. Earth. Mars, Saturn, and Titan. Specific atmospheric information is provided for these destinations, and example results are presented for the "back-of-the-envelope" calculations mentioned above.

Justus, Carl G.↗

AC motor and generator requirements for isolated WECS

After surveying electrically driven loads used on productive farms, the investigators chose three pumps for testing at voltages and frequencies far outside the normal operating range. These loads extract and circulate water and move heat via air, and all are critical to farm productivity. The object was to determine the envelope of supply voltage and frequency over which these loads would operate stably for time intervals under 1 hour. This information is among that needed to determine the feasibility of supplying critical loads, in case of a utility outage, from a wind driven alternator whose output voltage and frequency will vary dramatically in most continental wind regimes. Other related work is surveyed. The salient features and limitations of the test configurations used and the data reduction are described. The development of simulation models suitable for a small computer are outlined. The results are primarily displayed on the voltage frequency plane with the general conclusion that the particular pump models considered will operate over the range of 50 to 90 Hz and a voltage band which starts below rated, decreases as frequency decreases, and is limited on the high side by excessive motor heating. For example, centrifugal pump operating voltage ranges as extensive .4 to 1.4 appear possible. Particular problems with starting, stalling due to lack of motor torque, high speed cavitation, and likely overheating are addressed in a listing of required properties for wind driven alternators and their controllers needed for use in the isolated or stand alone configuration considered.

Park, G. L.↗

The Pressure Distribution over the Horizontal and Vertical Tail Surfaces of the F6C-4 Pursuit Airplane in Violent Maneuvers

This investigation of the pressure distribution on the tail surfaces of a pursuit airplane in violent maneuvers was conducted for the purpose of determining the maximum loads likely to be encountered on these surfaces in flight. The information is a part of that needed for a revision of existing loading specifications to bring these into closer agreement with the actual flight conditions. A standard F6C-4 airplane was used and the pressure distribution over the right horizontal and complete vertical tail surfaces was recorded throughout violent maneuvers. The results show that the existing loading specifications do not conform satisfactorily to the loadings existent in critical conditions, and in some cases were exceeded by the loads obtained. An acceleration of 10.5 G. Was recorded in one maneuver in which the pilot suffered severely; it is therefore indicated that the limits of the physical resistance of the pilot to violent maneuvers are being approached. Navy specifications for the structural design of tail surfaces are included as an appendix. (author)

Rhode, R V↗

Identification Uncertainty in Inverse Material Model Parameter Determination: A Sensitivity‐Based Decision Process for Load Path Selection

This research proposes a sensitivity-based framework for selecting the optimal prescribed loading path for a biaxial cruciform specimen. Optimality here is determined by the direction and magnitude of the prescribed displacement that minimizes the influence of random noise on the material model parameter identification. Using simulated experimental data based on finite element simulation, in this work, we identify the material model parameters of a Ludwik hardening model and plane stress implementation of the Hill-48 yield criterion using finite element model updating (FEMU). Our analysis reveals that the identification (or estimator) uncertainty of model parameters depends on the displacement boundary conditions (i.e., loading sequence) and the ground-truth value of the individual parameters. Optimal experimental design (OED) criteria based on the Fisher information matrix were investigated to mitigate indecision in the choice of optimal load path when the identification uncertainty of different material model parameters optimized at different load paths. The determinant of the Fisher information matrix was chosen here as the more useful metric due to its ability to capture uncertainty of the most influential material model parameters. The proposed framework demonstrates potential for real-time automated load step selection using scalar criteria derived prior to mechanical loading. The framework can be generalized to other geometries, boundary conditions and material models, allowing this procedure to be utilized for different experimental configurations and materials.

Fayad, Samuel S. [University of Illinois at Urbana↗