The restoration of constraints in holonomic and nonholonomic problems.
Constraint restoration in holonomic and nonholonomic problems involving system of algebraic or transcendental equations or first order differential equations
Damoulakis, J. N.↗
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Results for “system restoration”
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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The 3.3 micron emission feature: Map of the galactic disk, 10 deg less than 1 less than 35 deg, - 6 deg less than b less than 6 deg
The 3.3 micron aromatic feature has been detected in the diffuse galactic emission with the AROME balloon-borne instrument. The results are presented in the form of an map of the 3.3 micron feature's intensity. The AROME instrument consists in a Cassegrain telescope with wobbling secondary mirrors and a liquid/solid nitrogen cooled photometer. The instrumental output is modified by the impulse response of the system. So the galactic surface brightness was restored in Fourier space by an inverse optimal filtering. The map of the feature's intensity is presented for a region of galactic coordinates. All the known H II giant molecular cloud complexes are visible in the 3.3 micron feature emission showing a good correlation with the infrared dust emission.
Giard, Martin↗
Successful combination of the stochastic linearization and Monte Carlo methods
A combination of a stochastic linearization and Monte Carlo techniques is presented for the first time in literature. A system with separable nonlinear damping and nonlinear restoring force is considered. The proposed combination of the energy-wise linearization with the Monte Carlo method yields an error under 5 percent, which corresponds to the error reduction associated with the conventional stochastic linearization by a factor of 4.6.
Elishakoff, I.↗
Thrust Stand for Electric Propulsion Performance Evaluation
An electric propulsion thrust stand capable of supporting testing of thrusters having a total mass of up to 125 kg and producing thrust levels between 100 microN to 1 N has been developed and tested. The design features a conventional hanging pendulum arm attached to a balance mechanism that converts horizontal deflections produced by the operating thruster into amplified vertical motion of a secondary arm. The level of amplification is changed through adjustment of the location of one of the pivot points linking the system. Response of the system depends on the relative magnitudes of the restoring moments applied by the displaced thruster mass and the twisting torsional pivots connecting the members of the balance mechanism. Displacement is measured using a non-contact, optical linear gap displacement transducer and balance oscillatory motion is attenuated using a passive, eddy-current damper. The thrust stand employs an automated leveling and thermal control system. Pools of liquid gallium are used to deliver power to the thruster without using solid wire connections, which can exert undesirable time-varying forces on the balance. These systems serve to eliminate sources of zero-drift that can occur as the stand thermally or mechanically shifts during the course of an experiment. An in-situ calibration rig allows for steady-state calibration before, during and after thruster operation. Thrust measurements were carried out on a cylindrical Hall thruster that produces mN-level thrust. The measurements were very repeatable, producing results that compare favorably with previously published performance data, but with considerably smaller uncertainty.
Polzin, Kurt A.↗
AI-Enabled Operations at Fermi Complex: Multivariate Time Series Prediction for Outage Prediction and Diagnosis
The Main Control Room of the Fermilab accelerator complex continuously gathers extensive time-series data from thousands of sensors monitoring the beam. However, unplanned events such as trips or voltage fluctuations often result in beam outages, causing operational downtime. This downtime not only consumes operator effort in diagnosing and addressing the issue but also leads to unnecessary energy consumption by idle machines awaiting beam restoration. The current threshold-based alarm system is reactive and faces challenges including frequent false alarms and inconsistent outage-cause labeling. To address these limitations, we propose an AI-enabled framework that leverages predictive analytics and automated labeling. Using data from $2,703$ Linac devices and $80$ operator-labeled outages, we evaluate state-of-the-art deep learning architectures, including recurrent, attention-based, and linear models, for beam outage prediction. Additionally, we assess a Random Forest-based labeling system for providing consistent, confidence-scored outage annotations. Our findings highlight the strengths and weaknesses of these architectures for beam outage prediction and identify critical gaps that must be addressed to fully harness AI for transitioning downtime handling from reactive to predictive, ultimately reducing downtime and improving decision-making in accelerator management.
Jain, Milan [PNL, Richland] (ORCID:000000021676111↗
Water metabolism regulating mechanisms in hypokinesia
The range of daily fluctuations of the proportion of the amount of consumed water and its content in the body was evaluated by means of a water metabolism regulation factor. This index constitutes a relative measure of fluctuations of the constant of tritium water elimination from the body per 24 hours. It is established that under conditions of long term hypokinesia regulation of water metabolism is disturbed both in humans and in animals. Still more marked changes are observed 2 to 3 weeks after restoration of motor activity. The shifts noted are evidence of general biological regularity of disturbance of regulation systems in long term restriction of motor activity and in the early restoration period.
Krotov, V. P.↗
Novel Fault Location Method for Power Systems Based on Attention Mechanism and Double Structure GRU Neural Network
Fault location is one of the most essential techniques to maintain the stable operation of power systems. A fast and accurate fault location allows operators to restore power grids faster and avoid economic losses. Conventional methods rely on expert knowledge to extract the necessary features (e.g. DWT, DFT). For large systems, more coupling effects of transmission lines require more complex feature engineering, and incomplete features can easily introduce large errors. To overcome this, a deep learning approach without manual feature extraction is introduced to the fault location model under big data application. Towards this end, in the proposed method, the attention mechanism, the Bi-GRU and a dual structure network are applied to analyze the current data from different perspectives. Complete information for the fault features is extracted for the fault location. Based on a time series model and benefit from the ability to internally acquire the information architecture of faulty line, the established model is adaptive to the power grids with very complex topologies. Simulation results indicate that the proposed double-structure model reduces the maximum error and is less affected by noise. In comparison with different structures and different models, the proposed method shows better performance in IEEE 39-bus system.
42 ENGINEERING↗
Image gathering and restoration - Information and visual quality
A method is investigated for optimizing the end-to-end performance of image gathering and restoration for visual quality. To achieve this objective, one must inevitably confront the problems that the visual quality of restored images depends on perceptual rather than mathematical considerations and that these considerations vary with the target, the application, and the observer. The method adopted in this paper is to optimize image gathering informationally and to restore images interactively to obtain the visually preferred trade-off among fidelity resolution, sharpness, and clarity. The results demonstrate that this method leads to significant improvements in the visual quality obtained by the traditional digital processing methods. These traditional methods allow a significant loss of visual quality to occur because they treat the design of the image-gathering system and the formulation of the image-restoration algorithm as two separate tasks and fail to account for the transformations between the continuous and the discrete representations in image gathering and reconstruction.
Mccormick, Judith A.↗
Comparing restored HST and VLA imagery of R Aquarii
The maximum entropy method is applied to Hubble Space Telescope data taken of the R Aquarii binary system and its jet with the Faint Object Camera in order to restore an image in forbidden O III at 5007 A plagued by spherical aberration and detector saturation. These results are compared with 2-cm radio continuum imagery taken with the Very Large Array at the same limiting resolution of about 0.1 arcsec. The comparison suggests that shock excitation of the inner jet accounts for a spatial difference between the forbidden O III and radio continuum emission regions.
Hollis, J. M.↗
Metabolic Control Technology: Through the Windows of Space Exploration
As human presence in space will likely extend throughout the solar system, upmass and power constraints will become of paramount importance in considering logistics of transporting experimental animals and humans into space. Life support costs will be a significant part of the mission payload. One solution may be to take advantage of the emerging science of metabolic control, which allows the metabolism of animals to be reduced to a minimal level for a period of time, and allows for subsequent restoration to normal levels. Integration of a hibernation system within deep space mission architecture will solve many problems associated with long-duration space missions, such as payload cost reduction, space flight duration logistics, and demonstrate the potential application of this technology for human astronauts.
Griko, Yuri↗
Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems
Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A nonparametric identification method for a class of non-linear systems
A relatively simple nonparametric method for the identification of a class of close-coupled nonlinear multi-degree-of-freedom systems has been developed. The identification of arbitrary memoryless nonlinearities is possible through knowledge of the accelerations, velocities, and displacements of the various masses. These quantities are used to obtain the surfaces of the restoring forces as functions of the intermass displacements and velocities. The method was demonstrated by application to a four-degree-of-freedom system to identify the restoring forces. It is found that the identification results are relatively insensitive to measurement noise.
Udwadia, F. E.↗
Environmental Program
NASA's White Sands Test Facility has six core environmental compliance capabilities: remote hazardous testing of reactive, explosive and toxic materials and fluids; hypergolic fluids materials and systems testing; oxygen materials and system testing; hypervelocity impact testing; flight hardware processing; and, propulsion testing. The facility's permit status and challenges are reviewed. Historic operations and practices dating from the 1960s through the early 1980s resulted in contamination of the facility's groundwater. An environmental restoration effort has been employed to protect public health and the health of the workforce. The restoration seeks to properly handle hazardous materials and waste processes; determine the nature and extent of the contamination; stop the migration of contaminated groundwater; stabilize the plume front which has been assessed as the greatest risk to public health; and, clean-up the environment to restore it to preexisting conditions. The Plume Front Treatment System is operational and seeks to stop the westward movement of the plume to protect drinking water and irrigation well. Specifically, the treatment system will extract contaminated water from the aquifer, remove chemical using the best available technology, and return (inject) the treated water back to the aquifer. The Mid-Plume Interception Treatment System also seeks to stop the migration of containment, as well as to evaluate new technologies to accelerate cleanup, such as bioremediation.
Fischer, Holger↗
Vibration Reduction of Helicopter Blade Using Variable Dampers: A Feasibility Study
In the report, the investigation of controlling helicopter-blade lead-lag vibration is described. Current practice of adding passive damping may be improved to handle large dynamic range of the blade with several peaks of vibration resonance. To minimize extra-large damping forces that may damage the control system of blade, passive dampers should have relatively small damping coefficients, which in turn limit the effectiveness. By providing variable damping, a much larger damping coefficient to suppress the vibration can be realized. If the damping force reaches the maximum allowed threshold, the damper will be automatically switched into the mode with smaller damping coefficient to maintain near-constant damping force. Furthermore, the proposed control system will also have a fail-safe feature to guarantee the basic performation of a typical passive damper. The proposed control strategy to avoid resonant regions in the frequency domain is to generate variable damping force in combination with the supporting stiffness to manipulate the restoring force and conservative energy of the controlled blade system. Two control algorithms are developed and verified by a prototype variable damper, a digital controller and corresponding algorithms. Primary experiments show good potentials for the proposed variable damper: about 66% and 82% reductions in displacement at 1/3 length and the root of the blade respectively.
Lee, George C.↗
Minimum permissible leakage resistance established for instrumentation systems
Mathematical formulas are used to determine if, and to what extent, an instrumentation system that has been exposed to the elements should be dried out to restore minimum permissible leakage resistance to ground. Formulas are also derived and used for an intermediate number of systems that are exposed to moisture penetration.
Perrin, J. L.↗
Electromagnetically levitated vibration isolation system for the manufacturing process of silicon monocrystals
This paper introduces a study on an Electromagnetically Levitated Vibration Isolation System (ELVIS) for isolation control of large-scale vibration. This system features no mechanical contact between the isolation table and the installation floor, using a total of four electromagnetic actuators which generate magnetic levitation force in the vertical and horizontal directions. The configuration of the magnet for the vertical direction is designed to prevent any generation of restoring vibratory force in the horizontal direction. The isolation system is set so that vibration control effects due to small earthquakes can be regulated to below 5(gal) versus horizontal vibration levels of the installation floor of up t 25(gal), and those in the horizontal relative displacement of up to 30 (mm) between the floor and levitated isolation table. In particular, studies on the relative displacement between the installation floor and the levitated isolation table have been made for vibration control in the horizontal direction. In case of small-scale earthquakes (Taft wave scaled: max. 25 gal), the present system has been confirmed to achieve a vibration isolation to a level below 5 gal. The vibration transmission ratio of below 1/10 has been achieved versus continuous micro-vibration (approx. one gal) in the horizontal direction on the installation floor.
Kanemitsu, Yoichi↗
Enhancing Local Grid Resilience with Small Hydropower Hybrids: Proving the concept through demonstration, simulation, and analysis with Idaho Falls Power
Large hydropower, connected to the transmission system and typically possessing significant ability to balance grid frequency, has long been central to black start plans in regions where it is present. Small hydropower possesses most of the attributes required for black start but is often connected to distribution or sub-transmission systems and has less ability to balance grid frequency. Integrating energy storage such as batteries or ultracapacitors increases the combined asset’s ability to balance frequency. This asset integration enables a bottom-up grid restoration paradigm in which critical electric loads on the local distribution system can be powered even when the regional transmission system is down. This report presents a field demonstration conducted with Idaho Falls Power that proved this concept. The contribution of energy storage in restoring the small hydro-dominated distribution grid and its operational sensitivity across different control settings are further analyzed using high-fidelity simulations. Readers will learn about technical details on the field demonstration setup, energy storage contribution to black start, detailed simulation steps of islanded distribution grid restoration, and usage of field demonstration measurements for transient model refinements. Collectively this report points to a great opportunity for small hydropower to enhance resilience of local electric grids.
13 HYDRO ENERGY↗
Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning
Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.
Accumulated Local Effects↗