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At least 1,171 records · Page 65

A multiresolution adaptive wavelet method for nonlinear partial differential equations

We report the multiscale complexity of modern problems in computational science and engineering can prohibit the use of traditional numerical methods in multi-dimensional simulations. Therefore, novel algorithms are required in these situations to solve partial differential equations (PDEs) with features evolving on a wide range of spatial and temporal scales. To meet these challenges, we present a multiresolution wavelet algorithm to solve PDEs with significant data compression and explicit error control. We discretize in space by projecting fields and spatial derivative operators onto wavelet basis functions. We provide error estimates for the wavelet representation of fields and their derivatives. Then, our estimates are used to construct a sparse multiresolution discretization which guarantees the prescribed accuracy. Additionally, we embed a predictor-corrector procedure within the temporal integration to dynamically adapt the computational grid and maintain the accuracy of the solution of the PDE as it evolves. We present examples to highlight the accuracy and adaptivity of our approach.

97 MATHEMATICS AND COMPUTING↗

The Alamo multiphysics solver for phase field simulations with strong-form mechanics and block structured adaptive mesh refinement

Alamo is a high-performance scientific code that uses block-structured adaptive mesh refinement to solve such problems as: the ignition and burn of solid rocket propellant, plasticity, damage and fracture in materials undergoing loading, and the interaction of compressible flow with eroding solid materials. Alamo is powered by AMReX, and provides a set of unique methods, models, and algorithms that enable it to solve solid-mechanics problems (coupled to other physical behavior such as fluid flow or thermal diffusion) using the power of block-structured adaptive mesh refinement.

36 MATERIALS SCIENCE↗

Climate Adaptation Approaches for Water and Electric Utilities: A compendium of existing strategies in a changing climate

Report analyzes plans developed by water and electric utilities to address the impacts of changes in the climate within their service territories. The analysis identifies the main types of changes that utilities address, such as sea level rise, extreme heat, and compound events such as freezing rain/show and extreme wind events. It then identifies adaptation approaches utilities have proposed or adopted to address the changes that are anticipated in their service territories. The report also identifies the mechanisms utilities (and in some cases the governments which the utilities are part of) use to ensure that energy or environmental equity is increased as a result of the resilience program. In summary, the report provides a compendium of adaptation strategies that can be used by others as they review their own need to increase climate resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluations of Connectors, Inlets, and Adapters on Side-Load and Withstand Force

This report examines the mechanical forces that direct current fast charging (DCFC) electric vehicle supply equipment (EVSE) connectors and electric vehicle (EV) inlet ports experience during normal usage. As we witness the fast and growing variety of EVs, charge port locations, and bigger and more powerful EVSE configurations including the SAE J3400 North American Charging Standard (NACS), which has increased the use of adapters with J3400 and J1772 compatibility. These new conditions contribute to increased mechanical forces due to their size, weight and lever arm effect, which creates the need to study and compare these forces to the limits on UL2251 and IEC 62196-1 standards. This report focuses solely on high power DC charging EVSE connectors, EV inlets and adapters for the specific compatibility cases on J3400 with J1772. We first describe the details of the 100N and the 750N side-load evaluations as described in the standards, then present the data obtained by replicating these tests to finally go into more detail on the findings and our recommendations.

100N↗

Improving robustness for model discerning synthesis process of uranium oxide with unsupervised domain adaptation

The quantitative characterization of surface structures captured in scanning electron microscopy (SEM) images has proven to be effective for discerning provenance of an unknown nuclear material. Recently, many works have taken advantage of the powerful performance of convolutional neural networks (CNNs) to provide faster and more consistent characterization of surface structures. However, one inherent limitation of CNNs is their degradation in performance when encountering discrepancy between training and test datasets, which limits their use widely. The common discrepancy in an SEM image dataset occurs at low-level image information due to user-bias in selecting acquisition parameters and microscopes from different manufacturers. Therefore, in this study, we present a domain adaptation framework to improve robustness of CNNs against the discrepancy in low-level image information. Furthermore, our proposed approach makes use of only unlabeled test samples to adapt a pretrained model, which is more suitable for nuclear forensics application for which obtaining both training and test datasets simultaneously is a challenge due to data sensitivity. Through extensive experiments, we demonstrate that our proposed approach effectively improves the performance of a model by at least 18% when encountering domain discrepancy, and can be deployed in many CNN architectures.

scanning electron microscopy↗

Evaluating the Adaptability of Reinforcement Learning Based HVAC Control for Residential Houses

Intelligent Heating, Ventilation, and Air Conditioning (HVAC) control using deep reinforcement learning (DRL) has recently gained a lot of attention due to its ability to optimally control the complex behavior of the HVAC system. However, more exploration is needed on understanding the adaptability challenges that the DRL agent could face during the deployment phase. Using online learning for such applications is not realistic due to the long learning period and likely poor comfort control during the learning process. Alternatively, DRL can be pre-trained using a building model prior to deployment. However, developing an accurate building model for every house and deploying a pre-trained DRL model for HVAC control would not be cost-effective. In this study, we focus on evaluating the ability of DRL-based HVAC control to provide cost savings when pre-trained on one building model and deployed on different house models with varying user comforts. We observed around 30% of cost reduction by pre-trained model over baseline when validated in a simulation environment and achieved up to 21% cost reduction when deployed in the real house. This finding provides experimental evidence that the pre-trained DRL has the potential to adapt to different house environments and comfort settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation

Deep learning has exhibited remarkable results across diverse areas. To understand its success, substantial research has been directed towards its theoretical foundations. Nev- ertheless, the majority of these studies examine how well deep neural networks can model functions with uniform regularities. In this paper, we explore a different angle: how deep neural networks can adapt to varying degrees of smoothness in functions and nonuni- form data distributions across different locations and scales. More precisely, we focus on a broad class of functions defined by nonlinear tree-based approximation methods. This class encompasses a range of function types, such as functions with uniform regularities and discontinuous functions. We develop nonparametric approximation and estimation theories for this class using deep ReLU networks. Our results show that deep neural networks are adaptive to the nonuniform smoothness of functions and nonuniform data distributions at different locations and scales. We apply our results to several function classes, and derive the corresponding approximation and generalization errors. The validity of our results is demonstrated through numerical experiments.

97 MATHEMATICS AND COMPUTING↗

An Adaptive System for Load Relief and Accurate Control of Launch Vehicles

An adaptive load relief control system for a SATURN type vehicle which significantly reduces aerodynamically induced structural loads without incurring excessive velocity dispersions has been studied. This control system utilizes pendulous accelerometers to measure the angle between the total vehicle acceleration vector and the vehicle body. This measurement is used to fly the vehicle along the nominal trajectory to minimize velocity dispersions. However, if unusually high values of wind velocity are encountered, the system will cause the vehicle to turn into the wind to reduce the lateral structural loads. Results of an anal6g computer study show that the adaptive system can reduce aerodynam3cally induced peak structural loads as much as 50 percent under those encountered using conventional control techniques. relief is used only when required, velocity dispersions are held to a minimum.

ADAPTIVE CONTROL SYSTEM↗

Conference on Adaptive Telemetry

Adaptive telemetry conference on adaptive data control and processing, prediction, data compression, encoding, decoding, and modulation.

TELEMETRY↗

Plant adaptation to low atmospheric pressures: potential molecular responses

There is an increasing realization that it may be impossible to attain Earth normal atmospheric pressures in orbital, lunar, or Martian greenhouses, simply because the construction materials do not exist to meet the extraordinary constraints imposed by balancing high engineering requirements against high lift costs. This equation essentially dictates that NASA have in place the capability to grow plants at reduced atmospheric pressure. Yet current understanding of plant growth at low pressures is limited to just a few experiments and relatively rudimentary assessments of plant vigor and growth. The tools now exist, however, to make rapid progress toward understanding the fundamental nature of plant responses and adaptations to low pressures, and to develop strategies for mitigating detrimental effects by engineering the growth conditions or by engineering the plants themselves. The genomes of rice and the model plant Arabidopsis thaliana have recently been sequenced in their entirety, and public sector and commercial DNA chips are becoming available such that thousands of genes can be assayed at once. A fundamental understanding of plant responses and adaptation to low pressures can now be approached and translated into procedures and engineering considerations to enhance plant growth at low atmospheric pressures. In anticipation of such studies, we present here the background arguments supporting these contentions, as well as informed speculation about the kinds of molecular physiological responses that might be expected of plants in low-pressure environments.

NASA Discipline Plant Biology↗

Skeletal adaptation to external loads optimizes mechanical properties: fact or fiction

The skeleton adapts to a changing mechanical environment but the widely held concept that bone cells are programmed to respond to local mechanical loads to produce an optimal mechanical structure is not consistent with the high frequency of bone fractures. Instead, the author suggests that other important functions of bone compete with mechanical adaptation to determine structure. As a consequence of competing demands, bone architecture never achieves an optimal mechanical structure. c2001 Lippincott Williams & Wilkins, Inc.

Review, Tutorial↗

Space motion sickness preflight adaptation training: preliminary studies with prototype trainers

Preflight training frequently has been proposed as a potential solution to the problem of space motion sickness. The paper considers successively the otolith reinterpretation, the concept for a preflight adaptation trainer and the research with the Miami University Seesaw, the Wright Patterson Air-Force Base Dynamic Environment Simulator and the Visually Coupled Airborne Systems Simulator prototype adaptation trainers.

NASA Discipline Neuroscience↗

Role of insulin-like growth factor-I in the regulation of skeletal muscle adaptation to increased loading

Adaptations in muscle mass stimulated by changes in muscle loading state entail alternations in the synthesis and degradation of myofiber proteins and the modulation of myonuclear number such that the ratio between the number of myonuclei and the size of the myofibers remains relatively constant. As depicted schematically in Figure 2.6, the literature regarding the role of IGF-in mediating muscle adaptation to alterations in loading state suggests the following conclusions: During periods of increased loading, myofibers upregulate the expression and secretion of IGF-I. Acting as an autocrine and/or paracrine growth factor, IGF-I stimulates myofiber anabolic processes. Acting as a paracrine growth factor, IGF-I also stimulates adjacent satellite cells to enter the cell cycle and proliferate. Continued myofiber production of IGF-I stimulates some satellite cells to differentiate and then fuse with myofibers, thus providing additional myonuclei in order to maintain or reestablish the myonucleus to myofiber size ratios of the enlarged myofibers.

Review, Academic↗

Sleep and vestibular adaptation: implications for function in microgravity

Optimal human performance depends upon integrated sensorimotor and cognitive functions, both of which are known to be exquisitely sensitive to loss of sleep. Under the microgravity conditions of space flight, adaptation of both sensorimotor (especially vestibular) and cognitive functions (especially orientation) must occur quickly--and be maintained--despite any concurrent disruptions of sleep that may be caused by microgravity itself, or by the uncomfortable sleeping conditions of the spacecraft. It is the three-way interaction between sleep quality, general work efficiency, and sensorimotor integration that is the subject of this paper and the focus of new work in our laboratory. To record sleep under field conditions including microgravity, we utilize a novel system called the Nightcap that we have developed and extensively tested on normal and sleep-disordered subjects. To perturb the vestibular system in ground-based studies, we utilize a variety of experimental conditions including optokinetic stimulation and both minifying and reversing goggle paradigms that have been extensively studied in relation to plasticity of the vestibulo-ocular reflex. Using these techniques we will test the hypothesis that vestibular adaptation both provokes and is enhanced by REM sleep under both ground-based and space conditions. In this paper we describe preliminary results of some of our studies.

NASA Discipline Neuroscience↗

A review of adaptive change in musculoskeletal impedance during space flight and associated implications for postflight head movement control

We present a review of converging sources of evidence which suggest that the differences between loading histories experienced in 1-g and weightlessness are sufficient to stimulate adaptation in mechanical impedance of the musculoskeletal system. As a consequence of this adaptive change we argue that we should observe changes in the ability to attenuate force transmission through the musculoskeletal system both during and after space flight. By focusing attention on the relation between human sensorimotor activity and support surfaces, the importance of controlling mechanical energy flow through the musculoskeletal system is demonstrated. The implications of such control are discussed in light of visual-vestibular function in the specific context of head and gaze control during postflight locomotion. Evidence from locomotory biomechanics, visual-vestibular function, ergonomic evaluations of human vibration, and specific investigations of locomotion and head and gaze control after space flight, is considered.

Review, Tutorial↗

Nutrition and human physiological adaptations to space flight

Space flight provides a model for the study of healthy individuals undergoing unique stresses. This review focuses on how physiological adaptations to weightlessness may affect nutrient and food requirements in space. These adaptations include reductions in body water and plasma volume, which affect the renal and cardiovascular systems and thereby fluid and electrolyte requirements. Changes in muscle mass and function may affect requirements for energy, protein and amino acids. Changes in bone mass lead to increased urinary calcium concentrations, which may increase the risk of forming renal stones. Space motion sickness may influence putative changes in gastro-intestinal-hepatic function; neurosensory alterations may affect smell and taste. Some or all of these effects may be ameliorated through the use of specially designed dietary countermeasures.

Review↗

An Efficient Implementation of Forward-Backward LMS Adaptive Line Enhancer

An efficient implementation of the forward-backward least mean square (FBLMS) adaptive line enhancer is presented. Without changing the characteristics of the FBLMS adaptive line enhancer, the proposed implementation technique reduces multiplications by 25 percent and additions by 12.5 percent in two successive time samples in comparison to that of the direct implementation in both prediction and weight control. It can be applied to acquisition and tracking in both stationary and nonstationary environments.

adaptive line enhancers signal acquisition trackin↗