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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Preliminary weight and costs of sandwich panels to distribute concentrated loads

Minimum mass honeycomb sandwich panels were sized for transmitting a concentrated load to a uniform reaction through various distances. The form skin gages were fully stressed with a finite element computer code. The panel general stability was evaluated with a buckling computer code labeled STAGS-B. Two skin materials were considered; aluminum and graphite-epoxy. The core was constant thickness aluminum honeycomb. Various panel sizes and load levels were considered. The computer generated data were generalized to allow preliminary least mass panel designs for a wide range of panel sizes and load intensities. An assessment of panel fabrication cost was also conducted. Various comparisons between panel mass, panel size, panel loading, and panel cost are presented in both tabular and graphical form.

Belleman, G.↗
NASA NTRS1986

Buckling behavior of compression-loaded symmetrically-laminated angle-ply plates with holes

An approximate analysis for buckling of a rectangular specially-orthotropic plate with a central circular hole is applied to symmetrically-laminated angle-ply plates. Results obtained from finite element analyses and experiments indicate that the approximate analysis predicts accurately the buckling loads of (+/-theta sub m)s plates with integer values of m not below 6 and with hole diameters up to 50 percent of the plate width. Moreover, the results indicate that the approximate analysis can be used to predict the buckling trends of plates with hole diameters up to 70 percent of the plate width. Results of a parametric study indicate the influence of hole size, plate aspect ratio, loading conditions, boundary conditions, and orthotropy on the buckling load. Results are also presented that indicate the relationship of the bending stiffness and the prebuckling load distribution to the buckling load of a plate with a hole.

Nemeth, M. P.↗
NASA NTRS2015

Pressure-Equalizing Cradle for Booster Rocket Mounting

A launch system and method improve the launch efficiency of a booster rocket and payload. A launch aircraft atop which the booster rocket is mounted in a cradle, is flown or towed to an elevation at which the booster rocket is released. The cradle provides for reduced structural requirements for the booster rocket by including a compressible layer, that may be provided by a plurality of gas or liquid-filled flexible chambers. The compressible layer contacts the booster rocket along most of the length of the booster rocket to distribute applied pressure, nearly eliminating bending loads. Distributing the pressure eliminates point loading conditions and bending moments that would otherwise be generated in the booster rocket structure during carrying. The chambers may be balloons distributed in rows and columns within the cradle or cylindrical chambers extending along a length of the cradle. The cradle may include a manifold communicating gas between chambers.

Rutan, Elbert L.↗
NASA NTRS2000

Bolted Double-Lap Composite Joints Under Mechanical and Thermal Loading

This study concerns the determination of the contact stresses and contact region around bolt holes and the bolt load distribution in single- and double-lap joints of composite laminates with arbitrarily located bolts under general mechanical loading conditions and uniform temperature change. The unknown contact stress distribution and contact region between the bolt and laminates and the interaction among the bolts require the bolt load distribution, as well as the contact stresses, to be as part of the solution. The present method is based on the complex potential theory and the variational formulation in order to account for bolt stiffness, bolt-hole clearance, and finite geometry of the composite laminates.

Kradinov, V.↗
DOE OSTI2021

Restoring Critical Loads In Resilient Distribution Systems using A Curriculum Learned Controller

In this paper, we propose a curriculum learned reinforcement learning (RL) controller to facilitate distribution system critical load restoration (CLR), leveraging RL's fast online response and its outstanding optimal sequential control capability. Like many grid control problems, CLR is complicated due to the large control action space and renewable uncertainty in a heavily constrained non-linear environment with strong intertemporal dependency. The nature of the problem oftentimes causes the RL policy to converge to a poor-performing local optimum if learned directly. To overcome this, we design a two-stage curriculum in which the RL agent will learn generation control and load restoration decision under different scenarios progressively. Via curriculum learning, the trained RL controller is expected to achieve a better control performance, with critical loads restored as rapidly and reliably as possible. Using the IEEE 13-bus test system, we illustrate the performance of the RL controller trained by the proposed curriculum-based method.

curriculum learning↗
DOE OSTI2022

Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)

Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.

Eseye, Abinet Tesfaye↗
DOE OSTI2022

Curriculum-based Reinforcement Learning for Distribution System Critical Load Restoration

This paper focuses on the critical load restoration problem in distribution systems following major outages. To provide fast online response and optimal sequential decision-making support, a reinforcement learning (RL) based approach is proposed to optimize the restoration. Due to the complexities stemming from the large policy search space, renewable uncertainty, and nonlinearity in a complex grid control problem, directly applying RL algorithms to train a satisfactory policy requires extensive tuning to be successful. To address this challenge, this paper leverages the curriculum learning (CL) technique to design a training curriculum involving a simpler steppingstone problem that guides the RL agent to learn to solve the original hard problem in a progressive and more effective manner. We demonstrate that compared with direct learning, CL facilitates controller training to achieve better performance. To study realistic scenarios where renewable forecasts used for decision-making are in general imperfect, the experiments compare the trained RL controllers against two model predictive controllers (MPCs) using renewable forecasts with different error levels and observe how these controllers can hedge against the uncertainty. Results show that RL controllers are less susceptible to forecast errors than the baseline MPCs and can provide a more reliable restoration process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1952

Buckling of Low Arches or Curved Beams of Small Curvature

A general solution, based on the classical buckling criterion, is given for the problem of buckling of low arches under a lateral loading acting toward the center of curvature. For a sinusoidal arch under sinusoidal loading, the critical load can be expressed exactly as a simple function of the beam dimension parameters. For other arch shapes and load distributions, approximate values of the critical load can be obtained by summing a few terms of a rapidly converging Fourier series. The effects of initial end thrust and axial and lateral elastic support are discussed. The buckling load based on energy criterion of Karman and Tsien is also calculated. Results for both the classical and the energy criteria are compared with experimental results.

Fung, Y C↗
DOE OSTI2021

Restoring Critical Loads in Resilient Distribution Systems Using a Curriculum Learned Controller: Preprint

In this paper, we propose a curriculum learned reinforcement learning (RL) controller to facilitate distribution system critical load restoration (CLR), leveraging RL's fast online response and its outstanding optimal sequential control capability. Like many grid control problems, CLR is complicated due to the large control action space and renewable uncertainty in a heavily constrained non-linear environment with strong intertemporal dependency. The nature of the problem oftentimes causes the RL policy to converge to a poor-performing local optimum if learned directly. To overcome this, we design a two-stage curriculum in which the RL agent will learn generation control and load restoration decision under different scenarios progressively. Via curriculum learning, the trained RL controller is expected to achieve a better control performance, with critical loads restored as rapidly and reliably as possible. Using the IEEE 13-bus test system, we illustrate the performance of the RL controller trained by the proposed curriculum-based method.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1992

Computational structures technology at Grumman: Current practice/future needs

The current practice for the design analysis of new airframe structural systems is to construct a master finite element model of the vehicle in order to develop internal load distributions. The inputs to this model include the geometry which is taken directly from CADAM and CATIA structural layout and aerodynamic loads and mass distribution computer models. This master model is sufficiently detailed to define major load paths and for the computation of dynamic mode shapes and structural frequencies, but not detailed enough to define local stress gradients and notch stresses. This master model is then used to perform structural optimization studies that will provide minimum weights for major structural members. The post-processed output from the master model, load, stress, and strain analysis is then used by structural analysts to perform detailed stress analysis of local regions in order to design local structure with all its required details. This local analysis consists of hand stress analysis and life prediction analysis with the assistance of manuals, design charts, computer stress and structural life analysis and sometimes finite element or boundary element analysis. The resulting design is verified by fatigue tests.

Pifko, Allan B.↗
NASA NTRS1973

BUCLASP 3: A computer program for stresses and buckling of heated composite stiffened panels and other structures, user's manual

The use of the computer program BUCLASP3 is described. The code is intended for thermal stress and instability analyses of structures such as unidirectionally stiffened panels. There are two types of instability analyses that can be effected by PAINT; (1) thermal buckling, and (2) buckling due to a specified inplane biaxial loading. Any structure that has a constant cross section in one direction, that may be idealized as an assemblage of beam elements and laminated flat and curved plate strip-elements can be analyzed. The two parallel ends of the panel must be simply supported, whereas arbitrary elastic boundary conditions may be imposed along any one or both external longitudinal side. Any variation in the temperature rise (from ambient) through the cross section of a panel is considered in the analyses but it must be assumed that in the longitudinal direction the temperature field is constant. Load distributions for the externally applied inplane biaxial loads are similar in nature to the permissible temperature field.

Tripp, L. L.↗
NASA NTRS1976

Technical and Economic Assessment of Span-Loaded Cargo Aircraft Concepts

The benefits are assessed of span distributed loading concepts as applied to future commercial air cargo operations. A two phased program is used to perform this assessment. The first phase consists of selected parametric studies to define significant configuration, performance, and economic trends. The second phase consists of more detailed engineering design, analysis, and economic evaluations to define the technical and economic feasibility of a selected spanloader design. A conventional all-cargo aircraft of comparable technology and size is used as a comparator system. The technical feasibility is demonstrated of the spanloader concept with no new major technology efforts required to implement the system. However, certain high pay-off technologies such as winglets, airfoil design, and advanced structural materials and manufacturing techniques need refinement and definition prior to application. In addition, further structural design analysis could establish the techniques and criteria necessary to fully capitalize upon the high degree of structural commonality and simplicity inherent in the spanloader concept.

Source record↗
DOE OSTI2020

Data-Driven Linear Parameter-Varying Modeling and Control of Flexible Loads for Grid Services: Preprint

Flexible loads have great potential to improve the power grid's flexibility and stability. To effectively control large ensembles of heterogeneous loads, reliable models thereof are required. The paper presents a data-driven modeling and control approach to manage flexible loads for providing grid services. We leverage a linear parameter-varying autoregressive moving average (LPV-ARMA) model to describe the aggregate load response, where the parameters in the model are used to capture external environment impacts (e.g., weather). A gain-scheduling feedback controller is then developed to adapt to environmental variations. This data-driven approach can be easily applied to different types of loads in various environmental conditions. In addition to the ensemble controller, distributed load controllers are designed to deliver grid services, while maintaining the quality of service of inherent load tasks. We demonstrate the work on the IEEE 37-node distribution system for real-time power regulation services through control of thermostatically controlled loads.

control↗
DOE OSTI2021

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS-based on real-time optimal power flow-controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗