Evaluation of refractory fabrics for flexible heat shields.
Testing machine for evaluating high temperature fabrics under dynamic loading and heating conditions
LOAD TESTING MACHINE↗
SEARCH · Engineering Papers
Results for “flexible load”
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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Effects of control laws and relaxed static stability on vertical ride quality of flexible aircraft
State variable techniques are utilized to generate the RMS vertical load factors for the B-52H and B-1 bombers at low level, mission critical, cruise conditions. A ride quality index is proposed to provide meaningful comparisons between different controls or conditions. Ride quality is shown to be relatively invariant under various popular control laws. Handling quality variations are shown to be major contributors to ride quality variations on both vehicles. Relaxed static stability is artificially implemented on the study vehicles to investigate its effects on ride quality. The B-52H ride quality is generally degraded when handling characteristics are automatically restored by a feedback control to the original values from relaxed stability conditions. The B-1 airplane shows little ride quality sensitivity to the same analysis due to the small rigid body contribution to load factors at the flight condition investigated.
Roberts, P. A.↗
Gust-response Analysis of an Airplane Including Wing Bending Flexibility
Explore the source record for details and available documents.
LOADS, GUST - WINGS↗
ENSAERO - A multidisciplinary program for fluid/structural interaction studies of aerospace vehicles
A computational procedure is developed that uses a moving zonal grid concept to model complex flexible aerospace vehicles. The Euler/Navier-Stokes equations are used to model the flow, and computations are made using efficient methods based on both central and upwind schemes. The structure is represented by a finite element method which can model general aerospace vehicles. Provisions are made to accommodate other disciplines such as controls and thermal loads. The code is capable of computing unsteady flows on flexible wings with vortical flows. Adaptation of this procedure for parallel processing and validation for complete aerospace configurations is in progress.
Guruswamy, G. P.↗
Space Shuttle Main Engine nozzle thermal protection system
Two of the three Space Shuttle Main Engine (SSME) nozzles are exposed to significant reentry aeroheating loads. To ensure reusability of the Nozzle Assembly, the nozzle primary structure must not exceed specific temperature limits. Due to the thermal, pressure, and dynamic flexing of the nozzle during a mission cycle, an appropriate insulating system must have significant flexibility. Recent missions have demonstrated nozzle reentry aeroheating rates and heat loads much higher than predictions, higher than the capability of the original insulating system. A new insulating system has been developed using similar materials in an aerodynamically 'smooth' shape to both reduce the incoming heating and increase radiation cooling.
Nordlund, R. M.↗
Rheology of concentrated fiber suspensions with a load-dependent friction coefficient
Here we investigate the effects of fiber aspect ratio, roughness, flexibility, and volume fraction on the rheology of concentrated suspensions in a steady shear flow using direct numerical simulations. We model the fibers as inextensible continuous flexible slender bodies with the Euler-Bernoulli beam equation governing their dynamics suspended in an incompressible Newtonian fluid. The fiber dynamics and fluid flow coupling is achieved using the immersed boundary method. In addition, the fiber surface roughness might lead to interfiber contacts, resulting in normal and tangential forces between the fibers, which follow Coulomb’s law of friction. The surface roughness is modeled as hemispherical protrusions on the fiber surfaces. Their deformation results in a normal load-dependent friction coefficient. Our simulations accurately predict the experimentally observed shear thinning in fiber suspensions. Furthermore, we find that the suspension viscosity η increases with increasing the volume fraction, roughness, fiber rigidity, and aspect ratio. The increase in η is the macroscopic manifestation of a similar increase in the microscopic contact contribution to the total stress with these parameters. In addition, we observe positive and negative first N 1 and second N 2 normal stress differences, respectively, with |N 2 | < |N 1 |, in agreement with previous experiments. Last, we propose a modified Maron-Pierce law to quantify the reduction in the jamming volume fraction by increasing the fiber aspect ratio and roughness. Our results and analysis establish the use of fiber surface tribology to tune the suspension flow behavior.
42 ENGINEERING↗
Job Scheduler-Driven Power Gateway for High Performance Computing
Power gateways in the form of a microgrid can incorporate multiple distributed energy resources (DER) in either grid forming or grid following mode and support high performance computing (HPC) power profiles including the large load-follow requirements observed in multi-user HPC systems. The microgrid’s flexibility to operate in either grid forming or grid following mode and to actively switch between these modes enables baseline power from multiple non-baseline DER while maintaining high power quality metrics for the HPC system. But this enormous flexibility in demand response and time of use shifting is generally programmed independently of any integration with an HPC job scheduler which can better inform the load shaping by the microgrid. While there are many existing approaches where the HPC job scheduler takes in information from the grid to make queue scheduling decisions, this work takes the opposite view and explores a scheduler where the jobs in the queue can directly impact the settings of the grid. Several HPC scheduler strategies are tested where the jobs in the queue directly impact the settings of a microgrid designed for HPC operation which is driving a datacenter with three classes of HPC architectures. The scheduler operation is shown using a microgrid with 64 kW of solar capacity and 320 kWh of battery over a period of 21 days operating with significant low-follow swings, a throttled grid, cloudy conditions, switching between grid following and grid forming modes, and a wide range of battery states-of-charge all while maintaining high quality power metrics. The scheduler provides a mechanism for the job queue to directly impact a power gateway like a microgrid and to improve HPC power outcomes such as maximizing renewable energy usage
microgrid↗
Optimal Renewable Resource Allocation and Load Scheduling of Resilient Communities
This paper presents a methodology for enhancing community resilience through optimal renewable resource allocation and load scheduling in order to minimize unserved load and thermal discomfort. The proposed control architecture distributes the computational effort and is easier to be scaled up than traditional centralized control. The decentralized control architecture consists of two layers: The community operator layer (COL) allocates the limited amount of renewable energy resource according to the power flexibility of each building. The building agent layer (BAL) addresses the optimal load scheduling problem for each building with the allowable load determined by the COL. Both layers are formulated as a model predictive control (MPC) based optimization. Simulation scenarios are designed to compare different combinations of building weighting methods and objective functions to provide guidance for real-world deployment by community and microgrid operators. The results indicate that the impact of power flexibility is more prominent than the weighting factor to the resource allocation process. Allocation based purely on occupancy status could lead to an increase of PV curtailment. Further, it is necessary for the building agent to have multi-objective optimization to minimize unserved load ratio and maximize comfort simultaneously.
model predictive control↗
End-Use Savings Shapes Measure Documentation: Thermostat Control for Load Shifting in Large Offices
This documentation focuses on a single end-use savings shape measure - thermostat control for load shifting. The thermostat control for load shifting measure applies heating and cooling temperature setpoint adjustment for pre-conditioning before the peak window. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start time of the peak window, and then adjusts the thermostat cooling or heating setpoints by a specified offset value from original schedules to precool or preheat the space , for a specified length of time before the start of peak window, and thus shifts load in the peak window to the pre-conditioning period. The measure is flexible and allows users to adjust the heating and cooling offset values and length of pre-conditioning period, but for this study, the load shifting strategy is applied as pre-cooling only (adjusting only cooling setpoints). The default adjustment for cooling setpoints is set to -1 degrees Celsius , and the default duration of pre-cooling is 1 hour. This measure is applicable to large offices equipped with electric HVAC system, which account for approximately 8.72% of the ComStock floor area. The thermostat control for load shifting measure demonstrates -1% daily peak demand reduction and 0% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Integrated Transportation-Energy Systems Modeling
Transportation is currently the least-diversified energy demand sector, with over 90% of global transportation energy use coming from petroleum product. After over a century of petroleum dominance, however, many leading experts anticipate major electrification trends that could disrupt the transportation energy demand landscape. These changes in electricity demand complement profound changes happening within electric power supply systems, including integration of variable renewables, distributed generation and storage, and greater participation in power system planning and operations from traditionally passive consumers. This broader context underscores the importance of understanding how transportation electrification will impact electricity demand, including changes in the load shapes that characterize the system and the opportunity to leverage flexible EV charging to more cost-effectively balance demand and supply. This talk provides an overview of recent findings on infrastructure requirements to support EV adoption, integration challenges and the impact of EV on power systems, and opportunities to leverage flexible (or smart) EV charging to support power system planning and operations.
ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
Structural Analysis of Pressurized Small Diameter Lines in a Random Vibration Environment
The pressurization and propellant feed lines for the Ares 1 Upper Stage Reaction and Roll Control Systems (ReCS and RoCS) were required to be in a high g-load random vibration flight environment. The lines connected the system components and were filled with both liquid hydrazine and gaseous helium. They are considered small and varied between one fourth to one inch in diameter. The random vibration of the lines was considered to be base excitation through the mating components and mounting hardware. It was found that reducing the amount of support structure for the lines added flexibility to the system and improved the line stresses from random vibration, but caused higher stresses from the static g-loads. The locations and number of brackets were optimized by analyzing the mode shapes of the lines causing high stresses. The use of brackets that only constrain motion in the direction of concern further reduced the stresses in the lines. Finite element analysis was used to perform the analysis. The lines were pre-stressed by temperature and internal pressure with fluid and insulation included as non-structural mass. Base excitation was added to the model using Power Spectral Density (PSD) data for the expected flight loads. The random vibration and static g-load cases were combined to obtain the total stress in the lines. This approach advances the state of the art in line analysis by using FEA to predict the stresses in the lines and to optimize the entire system based on the expected flight environment. Adding flexibility to lines has been used in piping system for temperature loads, but in flight environments flexibility has been limited for the static stresses. Adding flexibility to the system in a flight environment by reducing brackets has the benefit of reducing stresses and weight
Davis, Mark↗
Shaft flexibility effects on the forced response of a bladed-disk assembly
A model analysis approach is used to study the forced response of an actual flexible bladed-disk-shaft system. Both in-plane and out-of-plane flexible deformations of the bladed-disk assembly are considered, in addition to its rigid-body translations and rotations, resulting from the bending of the supporting flexible shaft in two orthogonal planes. The effects of Coriolis forces and structural coupling between flexible and rigid disk motions on the system's response are investigated. Aerodynamic loads acting on the rotating and vibrating bladed-disk assembly are accounted for through a simple quasi-steady representation, to evaluate their influence, combined with shaft flexibility and Coriolis effects.
Khader, N.↗
Estimating Flexibility Envelopes for Residential Customers From Utility Smart Meter Data: Preprint
Demand response from residential customers has significant potential to support power system operations, but accurate flexibility estimation is challenging due to the limited resolution of advanced metering infrastructure (AMI) data. Most utility AMI measurements are recorded at hourly intervals, with only a small portion at higher resolutions, and even fewer households have appliance-level energy usage data. To address this issue, this paper proposes a two-stage long short-term memory (LSTM) framework for estimating household flexibility envelopes from low-resolution AMI data. In the first stage, the heating, ventilating, and air-conditioning (HVAC) load and non-HVAC loads are estimated by using a model trained on a small set of households with appliance-level profiles. These estimated data are then used to compute the upper- and lower-flexibility bounds, which are subsequently down-sampled to lower-resolution data. In the second stage, these flexibility bounds serve as training inputs for another LSTM model, enabling direct prediction of flexibility envelopes for households with only hourly AMI data. This method is validated using Pecan Street data from two different areas, and the results demonstrate its applicability and effectiveness.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Dynamic Modeling of a Solar-To-Hydrogen Flexible High Temperature Steam Electrolysis Plant
Sustainble hydrogen production for use as a renewable combustible fuel and clean chemical feedstock is an important objective as the world moves towards a renewable energy future. High temperature steam electrolysis is a promising hydrogen production technology due to its reduced electric input that is offset by heat input into steam generation and steam superheating. An option to provide this heat is to use concentrating solar thermal technology that can sustainably provide heat input while renewable electricity is used for the electrolysis reaction. In this work, a solar-to-hydrogen high temperature steam electrolysis plant is designed and dynamically modeled, showing continuous hydrogen production by utilizing supplemental heating and efficient recuperative heating from the electrolysis product streams. Through this design, over 90% of the required heat input for the process can by met by a combination of solar and recuperative heat. Additionally, the plant can flexibility operate by ramping down hydrogen production and through flexible heat integration, which intelligently integrates solar heat based on solar conditions. Smooth operation with flexible hydrogen production is demonstrated which decreases electrical input during on-peak grid times and also decreases the total supplemental heat load over the course of a day from 26.1% to 24.5%. In addition, by using flexible heat integration, the plant can increase its solar heat usage by 4.1% relative to a base case. Both options for flexibility show efficient use of solar thermal energy to sustainably and continuously produce hydrogen.
Immonen, Jake (ORCID:0000000341231625)↗
Main bearing response in a waked 15-MW floating wind turbine in below-rated conditions
Increased wind turbine size raises unknowns related to structural flexibility. Moreover, moving to deeper waters, component reliability becomes more critical. This work investigates main bearing response dependence on drivetrain flexibility and wake impingement in a two-turbine wind farm. A 15-MW floating direct-drive turbine is considered. Large eddy simulations (LES) are employed to model neutral, stable and unstable atmospheric conditions at below-rated mean wind speed, while the engineering codes OpenFAST and FAST.Farm simulate turbine and wake behavior. Results indicate significant sensitivities in fatigue estimates to lateral distance between the upstream and downstream turbine. The trends are most substantial in stable conditions, where the waked downwind main bearing sees twice the fatigue damage estimates of the upstream turbine for one position and 50% for another. Main bearing fatigue sensitivity to drivetrain flexibility is minor, while properly including generator rotor inertia loads is important for the axial forces of the locating (axially fixed) bearing, especially in stable conditions.
17 WIND ENERGY↗
Performance of multifunctional piezoelectric energy harvesting microgyroscopes with material degradation
Most microelectromechanical systems (MEMS) are made from brittle materials that are prone to cracking. Damage from the formation of cracks can occur anytime during the manufacturing process or due to mechanical loading of MEMS devices. Cracks can increase the structures flexibility and lead to changes in performance or total failure. Understanding the potential influences cracks in MEMS is necessary for the longevity of these systems. The energy harvesting microgyroscope studied in this work is susceptible to crack propagation in its silicon substrate and lead zirconate titanate piezoelectric patch. To this end, an electromechanical model is developed to capture the impacts of cracks on the performance of a damaged energy harvesting microgyroscope. Numerical methods are used to approximate the damage associated with distributed crack networks. Then, the static and dynamic responses of the damaged microgyroscope are analyzed for two possible multifunctional setups. Here, the current study revealed that cracks can significantly affect the static and dynamic behaviors of the microgyroscope energy harvester. Combinations of cracking and piezoelectric property degradation cause a decrease in the static pull-in voltage and shift the resonance frequencies of the system. Additionally, it is shown that the systems sensitivity to changes in the base rotation and energy harvesting capabilities vary widely depending on the severity of material degradation.
36 MATERIALS SCIENCE↗
Electrifying education: Exploring the electrification potential of U.S. School bus fleets
We analyze the operations of 270 diesel school buses across the United States to assess their electrification potential and evaluate the impact of various charging strategies on electricity demand. We find that school buses typically follow a two-route schedule on weekdays, featuring extended dwell times between morning and evening trips. Weekday trip distances average 25 miles, while weekend trips average 42 miles. Charging simulations indicate over 90% of the U.S. school bus fleet could be electrified using current technologies (300-mile range at 1.21 kWh/mile with 19.2-kW depot charging) without modifying existing operating patterns. Depot charging is a key enabler of school bus electrification, however, the strategic placement of charging stations at other locations (e.g., schools) can further increase electrification potential. Additionally, we find electric school bus charging to be highly flexible, with charge management capable of reducing peak charging loads at depots by up to 77%.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Coordinated Ramping Product and Regulation Reserve Procurements in CAISO and MISO using Multi-Scale Probabilistic Solar Power Forecasts (Pro2R)
How can probabilistic solar forecasts lower costs and improve reliability for independent system operator (ISO) markets? We tackle this question in three steps. First, we enhance an existing solar forecasting system to provide well-calibrated hours-ahead probabilistic forecasts. We then relate the degree of uncertainty in those forecasts to error distributions for net load ramps for the California ISO (CAISO) using statistical and machine learning methods. Projected net load errors conditioned on solar uncertainty are translated into flexible ramp requirements that therefore reflect real-time meteorological and solar conditions, improving on typical ISO procedures. Finally, a multi-period look-ahead production cost model quantifies how conditional ramp requirements can a) decrease operating costs by lowering requirements compared to often conservative unconditional methods, and b) reduce generation scarcity events and consequently improve reliability by increasing flexibility requirements at times when unconditional forecast-based requirements understate actual ramp uncertainty. In addition to the products just described (quantification of solar uncertainty, its translation into requirements for ramp capability product, and quantification of the benefits of more accurate ramp requirements), this project also developed a visualization system that alerts system operators of ramp and uncertainty conditions within the network based on solar forecasts. The system is called Resource Forecast and Ramp Visualization for Situational Awareness (RaVIS). These four products represent significant advances in the state-of-the-art of probabilistic solar forecasting, development of weather-informed reserve requirements, production costing methods for estimating the benefits of more accurate reserve requirements, and visualization of system status, respectively. Yet the products are also practical and can be immediately implemented, potentially enabling system operators to save millions of dollars in ramp product procurement costs per year.
14 SOLAR ENERGY↗