Load sharing energy savings methodology for systems with multiple centrifugal compressors
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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth
A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.
Dawicke, D. S.↗
Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs
Computational bioinformatics and biomedical applications frequently contain heterogeneously sized units of work or tasks, for instance due to variability in the sizes of biological sequences and molecules. Variable-sized workloads lead to load imbalances in parallel implementations which detract from efficiency and performance. Many modern computing resources now have multiple graphics processing units(GPUs) per computer for acceleration. These multiple GPU resources need to be used efficiently through balancing of workloads across the GPUs. OpenMP is a portable directive-based parallel programming API used ubiquitously in bioscience applications to program CPUs; recently, the use of OpenMP directives for GPU acceleration has become possible. Here, motivated by experiences with imbalanced loads in GPU-accelerated bioinformatics applications, we address the load balancing problem using OpenMP task-to-GPU scheduling combined with OpenMP GPU offloading for multiply heterogeneous workloads – loads with both variable input sizes, and simultaneously, variable convergence rates for algorithms with a stochastic component – scheduled across multiple GPUs. We aim to develop strategies which are both easy to use and have lower overheads, and may be incorporated incrementally in existing programs which already make use of OpenMP for CPU-based threading in order to make use of multi-GPU computers. We test different combinations of input size variability and convergence rate variability, and characterize the effects of these different scenarios on the performance of scheduling strategies across multiple GPUs with OpenMP. We present several dynamic scheduling solutions for different parallel patterns, explore optimizations, and provide publicly available example computational kernels to make these strategies easy to use in programs. This work will enable application developers to efficiently and easily use multiple GPUs for imbalanced workloads found in bioinformatics and biomedical applications.
Thavappiragasam, Mathialakan↗
Quantifying Solar PV Variability at Multiple Timescales for Power Systems Studies: Preprint
Increasing penetration of solar photovoltaics (PV) has concerned power system operators about their ability to balance load and generation over multiple timescales and maintain acceptable frequency profile because of the variability and uncertainty associated with solar PV. This paper focuses on developing metrics to quantify solar PV variability at multiple temporal scales ranging from seconds to an hour to help power system operators and planners better understand and account for solar PV variability under high solar PV penetration. Fourier coefficients of solar irradiation spectrum and average size of solar irradiation ramps over a day are the two metrics that are used to quantity the variability. It is shown that by using the two metrics the days with highest and lowest solar irradiation variability can be identified, which is useful information for operations planning or long-term power system planning studies. The key findings of the paper are (i) single sensor-based variability quantification can significantly exaggerate the variability of a solar PV plant, particularly at seconds to 1-min temporal resolution, (ii) at 1-minute or lower temporal resolutions, single sensor-based variability quantification of an entire plant can be fairly accurate, with the accuracy increasing as the temporal resolution reduces from 1-minute to 1-hour, (iii) at each 1-minute and lower temporal resolutions, maximum solar irradiation ramps appear to be independent of the geographical location of the sensor, and (iv) significant reduction in solar PV plant variability over a region with multiple plants is possible at all temporal scales, but more high quality, high temporal resolution data is needed to quantify the reduction with high confidence.
photovoltaics↗
Comparison of Coupled and Uncoupled Modeling of Floating Wind Farms with Shared Anchors
As design options for floating wind farms continue to be explored, shared (or multiline) anchors that secure mooring lines from multiple turbines remain a promising technology that can potentially reduce the number of anchors and overall mooring costs. This study evaluates two methods for analyzing the loads on shared anchors: one in which floating offshore wind turbines are simulated individually (using the software OpenFAST), and one in which an entire floating wind farm is simulated collectively (using the software FAST.Farm). A three-line shared anchor is evaluated for multiple loading scenarios in deep water, using the International Energy Agency 15 MW turbine on the VolturnUS-S semisubmersible platform. While the two methods produce broadly comparable results, the coupled wave loading on platforms within the farm results in wave force cancellations and amplifications that decrease multiline force directional ranges and increase multiline force extreme values (up to 7%) and standard deviations (up to 11%) for wave-driven load cases. The inclusion of wakes in FAST.Farm also reduces the net load on the shared anchor due to the velocity deficit, leading to larger differences between OpenFAST and FAST.Farm (up to 3% difference in mean loads) for load cases with operational turbines.
17 WIND ENERGY↗
Real-time forecasting of electricity demand in a streams-based architecture with applications
A streams platform is used. Multiple streams of electricity usage data are received, each from an electrical meter providing periodic updates to electrical usage for devices connected to the electrical meter. Weather information is received corresponding to locations where the electrical meters are. Real-time predictive modeling of electricity demand is performed based on the received multiple streams of electricity usage data and the received weather information, at least by performing: updating a state space model for electrical load curves using the usage data from the streams and the weather, wherein the updating uses current load observations for the multiple streams for a current time period; and creating forecast(s) for the electricity demand. The forecast(s) of the electricity demand are output. Appliance-level predictions may be made and used, and substitution effects and load management functions may be performed.
Ghosh, Soumyadip↗
Using Dynamic Simulation to Evaluate Attemperator Operation in a Natural Gas Combined Cycle With Duct Burners in the Heat Recovery Steam Generator
A generic training simulator of a natural gas combined cycle was modified to match operations at a real plant. The objective was to use the simulator to analyze cycling operations of the plant. Initial operation of the simulator revealed the potential for saturation conditions in the final high pressure superheater as the attemperator tried to control temperature at the superheater outlet during gas turbine loading and unloading. Subsequent plant operational data confirmed simulation results. Multiple simulations were performed during loading and unloading of the gas turbine to determine operational strategies that prevented saturation and increased the approach to saturation temperature. The solutions included changes to the attemperator temperature control setpoints and strategic control of the steam turbine inlet pressure control valve.
20 FOSSIL-FUELED POWER PLANTS↗
Composite Load Spectra for Select Space Propulsion Structural Components
Generic load models are described with multiple levels of progressive sophistication to simulate the composite (combined) load spectra (CLS) that are induced in space propulsion system components, representative of Space Shuttle Main Engines (SSME), such as transfer ducts, turbine blades and liquid oxygen (LOX) posts. These generic (coupled) models combine the deterministic models for composite load dynamic, acoustic, high-pressure and high rotational speed, etc., load simulation using statistically varying coefficients. These coefficients are then determined using advanced probabilistic simulation methods with and without strategically selected experimental data. The entire simulation process is included in a CLS computer code. Applications of the computer code to various components in conjunction with the PSAM (Probabilistic Structural Analysis Method) to perform probabilistic load evaluation and life prediction evaluations are also described to illustrate the effectiveness of the coupled model approach.
Ho, Hing W.↗
Improving stability and strength characteristics of framed structures with nonlinear behavior
In this paper an optimal design procedure is introduced to improve the overall performance of nonlinear framed structures. The design methodology presented here is a multiple-objective optimization procedure whose objective functions involve the buckling eigenvalues and eigenvectors of the structure. A constant volume with bounds on the design variables is used in conjunction with an optimality criterion approach. The method provides a general tool for solving complex design problems and generally leads to structures with better limit strength and stability. Many algorithms have been developed to improve the limit strength of structures. In most applications geometrically linear analysis is employed with the consequence that overall strength of the design is overestimated. Directly optimizing the limit load of the structure would require a full nonlinear analysis at each iteration which would be prohibitively expensive. The objective of this paper is to develop an algorithm that can improve the limit-load of geometrically nonlinear framed structures while avoiding the nonlinear analysis. One of the novelties of the new design methodology is its ability to efficiently model and design structures under multiple loading conditions. These loading conditions can be different factored loads or any kind of loads that can be applied to the structure simultaneously or independently. Attention is focused on optimal design of space framed structures. Three-dimensional design problems are more complicated to carry out, but they yield insight into real behavior of the structure and can help avoiding some of the problems that might appear in planar design procedure such as the need for out-of-plane buckling constraint. Although researchers in the field of structural engineering generally agree that optimum design of three-dimension building frames especially in the seismic regions would be beneficial, methods have been slow to emerge. Most of the research in this area has dealt with the optimization of truss and plane frame structures.
Pezeshk, Shahram↗
Maximizing TDRS Command Load Lifetime
The GNC software onboard ISS utilizes TORS command loads, and a simplistic model of TORS orbital motion to generate onboard TORS state vectors. Each TORS command load contains five "invariant" orbital elements which serve as inputs to the onboard propagation algorithm. These elements include semi-major axis, inclination, time of last ascending node crossing, right ascension of ascending node, and mean motion. Running parallel to the onboard software is the TORS Command Builder Tool application, located in the JSC Mission Control Center. The TORS Command Builder Tool is responsible for building the TORS command loads using a ground TORS state vector, mirroring the onboard propagation algorithm, and assessing the fidelity of current TORS command loads onboard ISS. The tool works by extracting a ground state vector at a given time from a current TORS ephemeris, and then calculating the corresponding "onboard" TORS state vector at the same time using the current onboard TORS command load. The tool then performs a comparison between these two vectors and displays the relative differences in the command builder tool GUI. If the RSS position difference between these two vectors exceeds the tolerable lim its, a new command load is built using the ground state vector and uplinked to ISS. A command load's lifetime is therefore defined as the time from when a command load is built to the time the RSS position difference exceeds the tolerable limit. From the outset of TORS command load operations (STS-98), command load lifetime was limited to approximately one week due to the simplicity of both the onboard propagation algorithm, and the algorithm used by the command builder tool to generate the invariant orbital elements. It was soon desired to extend command load lifetime in order to minimize potential risk due to frequent ISS commanding. Initial studies indicated that command load lifetime was most sensitive to changes in mean motion. Finding a suitable value for mean motion was therefore the key to achieving this goal. This goal was eventually realized through development of an Excel spreadsheet tool called EMMIE (Excel Mean Motion Interactive Estimation). EMMIE utilizes ground ephemeris nodal data to perform a least-squares fit to inferred mean anomaly as a function of time, thus generating an initial estimate for mean motion. This mean motion in turn drives a plot of estimated downtrack position difference versus time. The user can then manually iterate the mean motion, and determine an optimal value that will maximize command load lifetime. Once this optimal value is determined, the mean motion initially calculated by the command builder tool is overwritten with the new optimal value, and the command load is built for uplink to ISS. EMMIE also provides the capability for command load lifetime to be tracked through multiple TORS ephemeris updates. Using EMMIE, TORS command load lifetimes of approximately 30 days have been achieved.
Brown, Aaron J.↗
Mechanism of Lithium Ion Exchange Into Spinel Manganese Oxide
Lithium manganese oxide (LMO) is an effective absorbent for lithium recovery from brines, characterized by its high adsorption capacity, excellent regeneration performance, and selectivity. Here, this study investigates the mechanisms of material degradation during lithium loading and unloading in LMO, employing a combination of time‐resolved Raman spectroscopy, X‐ray diffraction, and X‐ray photoelectron spectroscopy. Key findings reveal that the A 1g vibrational mode wavenumber shifts from 635 cm −1 at the onset of lithium ion exchange to 656 cm −1 after 12 min, indicating local symmetry loss and manganese (Mn) loss during lithium intercalation. The proposed lithium exchange mechanism involves initial occupation of tetrahedral interstitial voids, followed by migration into interstitial sites between Mn octahedral sites. Computational modeling suggests that the loss of symmetry in MnO cubane‐like groups occurs as lithium migrates, significantly affecting the Raman spectra. Importantly, the study demonstrates that after 100 cycles of lithium/hydrogen loading, a 24% loss in Mn is observed, which correlates with decreased structural stability; however, the structural integrity of LMO is enhanced when subjected to multiple cycles without complete loading. Here, these insights contribute to the understanding of LMO's performance in lithium recovery applications and highlight potential strategies to optimize its use in future technologies.
15 GEOTHERMAL ENERGY↗
Multicyclic control of a helicopter rotor considering the influence of vibration, loads, and control motion
Weighted multiple linear regression is used to establish a transfer function matrix relationship between higher harmonic control inputs and transducer vibration outputs for a controllable twist rotor. Data used in the regression were taken from the test of a KAMAN controllable twist rotor conducted in the Ames Research Center's 40- by 80-Foot Wind Tunnel in June 1977. Optimal controls to minimize fixed system vibrational levels are calculated using linear quadratic regulatory theory with a control deflection penalty included in the performance criteria. Control sensitivity to changes in control travel, forward speed, and lift and propulsive forces is examined. It is found that the linear transfer matrix is a strong function of forward speed and a weak function of lift and propulsive force. An open-loop strategy is proposed for systems with limited control travel.
Brown, T. J.↗
Loads Model Development and Analysis for the F/A-18 Active Aeroelastic Wing Airplane
The Active Aeroelastic Wing airplane was successfully flight-tested in March 2005. During phase 1 of the two-phase program, an onboard excitation system provided independent control surface movements that were used to develop a loads model for the wing structure and wing control surfaces. The resulting loads model, which was used to develop the control laws for phase 2, is described. The loads model was developed from flight data through the use of a multiple linear regression technique. The loads model input consisted of aircraft states and control surface positions, in addition to nonlinear inputs that were calculated from flight-measured parameters. The loads model output for each wing consisted of wing-root bending moment and torque, wing-fold bending moment and torque, inboard and outboard leading-edge flap hinge moment, trailing-edge flap hinge moment, and aileron hinge moment. The development of the Active Aeroelastic Wing loads model is described, and the ability of the model to predict loads during phase 2 research maneuvers is demonstrated. Results show a good match to phase 2 flight data for all loads except inboard and outboard leading-edge flap hinge moments at certain flight conditions. The average load prediction errors for all loads at all flight conditions are 9.1 percent for maximum stick-deflection rolls, 4.4 percent for 5-g windup turns, and 7.7 percent for 4-g rolling pullouts.
Allen, Michael J.↗
Loads Model Development and Analysis for the F/A-18 Active Aeroelastic Wing Airplane
The Active Aeroelastic Wing airplane was successfully flight-tested in March 2005. During phase 1 of the two-phase program, an onboard excitation system provided independent control surface movements that were used to develop a loads model for the wing structure and wing control surfaces. The resulting loads model, which was used to develop the control laws for phase 2, is described. The loads model was developed from flight data through the use of a multiple linear regression technique. The loads model input consisted of aircraft states and control surface positions, in addition to nonlinear inputs that were calculated from flight-measured parameters. The loads model output for each wing consisted of wing-root bending moment and torque, wing-fold bending moment and torque, inboard and outboard leading-edge flap hinge moment, trailing-edge flap hinge moment, and aileron hinge moment. The development of the Active Aeroelastic Wing loads model is described, and the ability of the model to predict loads during phase 2 research maneuvers is demonstrated. Results show a good match to phase 2 flight data for all loads except inboard and outboard leading-edge flap hinge moments at certain flight conditions. The average load prediction errors for all loads at all flight conditions are 9.1 percent for maximum stick-deflection rolls, 4.4 percent for 5-g windup turns, and 7.7 percent for 4-g rolling pullouts.
Allen, Michael J.↗
Biomechanical Modeling of Split-leg Squat and Heel Raise on the Hybrid Ultimate Lifting Kit (HULK)
Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and musculoskeletal forces that occur during exercises performed on the prototype devices. Computational models currently use OpenSim software, an open source code for musculoskeletal modeling, with biomechanical input data from subjects for estimation of muscle and joint loads. Subjects are instrumented with reflective markers for motion capture data collection while exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device. Ground reaction force data is collected with force plates under the feet and device loading is recorded through load cells internal to the HULK. This data is input into the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the loads on the body. Multiple exercises are performed and evaluated during a test session such as a full squat, single leg squat, heel raise and dead lift. Variables for these exercises include applied device load, narrow or wide foot stance, slow or fast cadence and the harness or long bar interface between the test subject and the device. Data from free weights are compared to the resistively loaded exercise device. The focus of this presentation is to summarize the results from the single-leg squat and heel raise exercises performed during three sessions occurring in 2015. Differences in loading configuration, cadence and stance produce differences in kinematics, joint toques and force and muscle forces.
computational modeling↗
Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic
In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.
30 DIRECT ENERGY CONVERSION↗
EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation
The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.
15 GEOTHERMAL ENERGY↗
A comparative analysis of loop heat pipe based thermal architectures for spacecraft thermal control
Loop Heat Pipes (LHP) have gained acceptance as a viable means of heat transport in many spacecraft in recent years. However, applications using LHP technology tend to only remove waste heat from a single component to an external radiator. Removing heat from multiple components has been done by using multiple LHPs. This paper discusses the development and implementation of a Loop Heat Pipe based thermal architecture for spacecraft. In this architecture, a Loop Heat Pipe with multiple evaporators and condensers is described in which heat load sharing and thermal control of multiple components can be achieved. A key element in using a LHP thermal architecture is defining the need for such an architecture early in the spacecraft design process. This paper describes an example in which a LHP based thermal architecture can be used and how such a system can have advantages in weight, cost and reliability over other kinds of distributed thermal control systems. The example used in this paper focuses on a Mars Rover Thermal Architecture. However, the principles described here are applicable to Earth orbiting spacecraft as well.
loop heat pipes↗