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At least 559 records · Page 31

Advanced Signal Conditioners for Data-Acquisition Systems

Signal conditioners embodying advanced concepts in analog and digital electronic circuitry and software have been developed for use in data-acquisition systems that are required to be compact and lightweight, to utilize electric energy efficiently, and to operate with high reliability, high accuracy, and high power efficiency, without intervention by human technicians. These signal conditioners were originally intended for use aboard spacecraft. There are also numerous potential terrestrial uses - especially in the fields of aeronautics and medicine, wherein it is necessary to monitor critical functions. Going beyond the usual analog and digital signal-processing functions of prior signal conditioners, the new signal conditioner performs the following additional functions: It continuously diagnoses its own electronic circuitry, so that it can detect failures and repair itself (as described below) within seconds. It continuously calibrates itself on the basis of a highly accurate and stable voltage reference, so that it can continue to generate accurate measurement data, even under extreme environmental conditions. It repairs itself in the sense that it contains a micro-controller that reroutes signals among redundant components as needed to maintain the ability to perform accurate and stable measurements. It detects deterioration of components, predicts future failures, and/or detects imminent failures by means of a real-time analysis in which, among other things, data on its present state are continuously compared with locally stored historical data. It minimizes unnecessary consumption of electric energy. The design architecture divides the signal conditioner into three main sections: an analog signal section, a digital module, and a power-management section. The design of the analog signal section does not follow the traditional approach of ensuring reliability through total redundancy of hardware: Instead, following an approach called spare parts tool box, the reliability of each component is assessed in terms of such considerations as risks of damage, mean times between failures, and the effects of certain failures on the performance of the signal conditioner as a whole system. Then, fewer or more spares are assigned for each affected component, pursuant to the results of this analysis, in order to obtain the required degree of reliability of the signal conditioner as a whole system. The digital module comprises one or more processors and field-programmable gate arrays, the number of each depending on the results of the aforementioned analysis. The digital module provides redundant control, monitoring, and processing of several analog signals. It is designed to minimize unnecessary consumption of electric energy, including, when possible, going into a low-power "sleep" mode that is implemented in firmware. The digital module communicates with external equipment via a personal-computer serial port. The digital module monitors the "health" of the rest of the signal conditioner by processing defined measurements and/or trends. It automatically makes adjustments to respond to channel failures, compensate for effects of temperature, and maintain calibration.

Lucena, Angel↗

Space communication link propagation data for selected cities within the multiple beam and steerable antenna coverage areas of the advanced communications technology satellite

Rain attenuation propagation data for 68 cities within the coverage area of the multiple beam and steerable antennas of the Advanced Communications Technology Satellite (ACTS) are presented. These data provide the necessary data base for purposes of communication link power budgeting and rain attenuation mitigation controller design. These propagation parameters are derived by applying the ACTS Rain Attenuation Prediction Model to these 68 locations. The propagation parameters enumerated in tabular form for each location are as follows: (1) physical description of the link and location (e.g., latitude, longitude, antenna elevation angle, etc.), link availability versus attenuation margin (also in graphical form), fading time across fade depths of 3, 5, 8, and 15 dB versus fade duration, and required fade control response time for controller availabilities of 99.999, 99.99, 99.9, and 99 percent versus sub-threshold attenuation levels. The data for these specific locations can be taken to be representative of regions near these locations.

Manning, Robert M.↗

Thermal design verification testing for the ATS-F and -G spacecraft.

There is a wide fluctuation in the internal power dissipation from the components within the earth viewing module (EVM). The electronic component functional reliability required for a two-to-five year mission is the most significant factor for the thermal design criteria. A mathematical thermal model of the EVM and the orbital environment is used to predict the performance of the thermal control system. Comparisons of the results obtained in chamber thermal balance tests with the data computed on the basis of the theoretical model provide the means for validating the thermal design.

Coyle, M.↗

Assessment of a transitional boundary layer theory at low hypersonic Mach numbers

An investigation was carried out to assess the accuracy of a transitional boundary layer theory in the low hypersonic Mach number regime. The theory is based upon the simultaneous numerical solution of the boundary layer partial differential equations for the mean motion and an integral form of the turbulence kinetic energy equation which controls the magnitude and development of the Reynolds stress. Comparisions with experimental data show the theory is capable of accurately predicting heat transfer and velocity profiles through the transitional regime and correctly predicts the effects of Mach number and wall cooling on transition Reynolds number. The procedure shows promise of predicting the initiation of transition for given free stream disturbance levels. The effects on transition predictions of the pressure dilitation term and of direct absorption of acoustic energy by the boundary layer were evaluated.

Shamroth, S. J.↗

Simulation of an ion thruster control system

The results of an initial effort to model the control loops of a 30-cm diameter electron bombardment thruster and a transistorized power processor predicting its operation were described. Data from which the model is made is presented as well as comparisons between the computer outputs and test data from the JPL Solar Electric Propulsion systems laboratory.

Kudo, I.↗

Planning for large construction projects in space

The paper discusses briefly some broad plans for developing the technology needed for large construction projects in space ranging from orbiting solar power stations to large communications antennas. Space construction classes include assembly of modules, deployment of compacted structures, assembly of passive preformed pieces, and fabrication of structures from sheet stock. Technological areas related to structural concepts include (1) analyses for prediction of structural behavior, structural/control interaction, electromagnetic and control performance, and integrated design development; (2) electronics for signal conditioning and data acquisition, power distribution, and signal channel interference and multipaction; (3) concepts for shape control, attitude/pointing control, and orbital transfer and station keeping; and (4) materials and techniques for 30-year dimensional stable composites, thermal control, thin-lightweight structural alloys, and material joining in space. The concept of a power module for the construction operations is discussed along with a concept for a habitability module.

Disher, J. H.↗

Status and future plans of the Drones for Aerodynamic and Structural Testing (DAST) program

Results from flight tests of the ARW-1 research wing are presented. Preliminary loads data and experiences with the active control system for flutter suppression are included along with comparative results of test and prediction for the flutter boundary of the supercritical research wing and on performance of the flutter suppression system. The status of the ARW-2 research wing is given.

Murrow, H. N.↗

Combustion experiments in reduced gravity with two-component miscible droplets

The combustion of liquid fuels is a topic worthy of scientific attention on practical and fundamental grounds. Most practical applications of liquid-fuel combustion involve the formation of spray diffusion flames, where droplets frequently burn in groups rather than individually. The combustion is typically complex, with interactions occurring between various physical mechanisms. Many efforts to understand liquid sprays have focused upon studying isolated droplets. Information gained from these studies is often not directly transferable to spray situations. However, isolated-droplet studies are useful in that they allow certain phenomena (e.g., extinction) to be studied under well-controlled and simplified conditions. When theory and experiment agree for simplified situations, predictions for more complex cases (where accurate experimental data may not exist) may be made with more confidence. The simplest droplet combustion scenario is that of an isolated droplet undergoing spherically-symmetric combustion in an environment of infinite extent. The idealization is approached only when forced and buoyant convection are negligible, the droplet is unsupported, and all foreign objects are far-removed from the combustion zone. Appreciable gravity levels compromise spherical symmetry by inducing buoyant convection.

Shaw, Benjamin D.↗

Roughness Based Crossflow Transition Control: A Computational Assessment

A combination of parabolized stability equations and secondary instability theory has been applied to a low-speed swept airfoil model with a chord Reynolds number of 7.15 million, with the goals of (i) evaluating this methodology in the context of transition prediction for a known configuration for which roughness based crossflow transition control has been demonstrated under flight conditions and (ii) of analyzing the mechanism of transition delay via the introduction of discrete roughness elements (DRE). Roughness based transition control involves controlled seeding of suitable, subdominant crossflow modes, so as to weaken the growth of naturally occurring, linearly more unstable crossflow modes. Therefore, a synthesis of receptivity, linear and nonlinear growth of stationary crossflow disturbances, and the ensuing development of high frequency secondary instabilities is desirable to understand the experimentally observed transition behavior. With further validation, such higher fidelity prediction methodology could be utilized to assess the potential for crossflow transition control at even higher Reynolds numbers, where experimental data is currently unavailable.

Li, Fei↗

Computational Study of Laminar Flow Control on a Subsonic Swept Wing Using Discrete Roughness Elements

A combination of parabolized stability equations and secondary instability theory has been applied to a low-speed swept airfoil model with a chord Reynolds number of 7.15 million, with the goals of (i) evaluating this methodology in the context of transition prediction for a known configuration for which roughness based crossflow transition control has been demonstrated under flight conditions and (ii) of analyzing the mechanism of transition delay via the introduction of discrete roughness elements (DRE). Roughness based transition control involves controlled seeding of suitable, subdominant crossflow modes, so as to weaken the growth of naturally occurring, linearly more unstable crossflow modes. Therefore, a synthesis of receptivity, linear and nonlinear growth of stationary crossflow disturbances, and the ensuing development of high frequency secondary instabilities is desirable to understand the experimentally observed transition behavior. With further validation, such higher fidelity prediction methodology could be utilized to assess the potential for crossflow transition control at even higher Reynolds numbers, where experimental data is currently unavailable.

Li, Fei↗

Active Rack Isolation System Program and Technical Status

The Boeing Active Rack Isolation System (ARIS) is one of the means used to isolate acceleration-sensitive scientific experiments from structurally transmitted disturbances aboard the International Space Station. The presentation provides an overview of ARIS and technical issues associated with the development of the active control system. An overview of ARIS analytical models is presented along with recent isolation performance predictions made using these models. Issues associated with commanding and capturing ARIS data are discussed and possible future options based on the ARIS ISS Characterization Experiment (ICE) Payload On-orbit Processor (POP) are outlined. An overview of the ARIS-ICE experiment scheduled to fly on ISS Flight 6A is presented. The presentation concludes with a discussion of recent- developmental work that includes passive rack damping, umbilical redesigns and advanced multivariable control design methods.

Bushnell, Glenn↗

On methods for application of harmonic control

The paper presents data which confirm the effectiveness of higher harmonic blade pitch control in substantially reducing helicopter rotor vibratory hub loads. The data are the result of recent tests on a 2.7-m model conducted in the Langley Research Center's transonic dynamics wind tunnel. Several predictive analyses developed in support of the NASA program are shown capable of accurately predicting both amplitude and phase of the higher harmonic control input required to nullify a single 4/rev force or moment input. The use of multiple blade feathering inputs in the design of a flightworthy higher harmonic control system is discussed.

Wood, E. R.↗

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗

Predicting Kyasanur forest disease in resource-limited settings using event-based surveillance and transfer learning

In recent years, the reports of Kyasanur forest disease (KFD) breaking endemic barriers by spreading to new regions and crossing state boundaries is alarming. Effective disease surveillance and reporting systems are lacking for this emerging zoonosis, hence hindering control and prevention efforts. We compared time-series models using weather data with and without Event-Based Surveillance (EBS) information, i.e., news media reports and internet search trends, to predict monthly KFD cases in humans. We fitted Extreme Gradient Boosting (XGB) and Long Short-Term Memory models at the national and regional levels. We utilized the rich epidemiological data from endemic regions by applying Transfer Learning (TL) techniques to predict KFD cases in new outbreak regions where disease surveillance information was scarce. Overall, the inclusion of EBS data, in addition to the weather data, substantially increased the prediction performance across all models. The XGB method produced the best predictions at the national and regional levels. The TL techniques outperformed baseline models in predicting KFD in new outbreak regions. Novel sources of data and advanced machine-learning approaches, e.g., EBS and TL, show great potential towards increasing disease prediction capabilities in data-scarce scenarios and/or resource-limited settings, for better-informed decisions in the face of emerging zoonotic threats.

60 APPLIED LIFE SCIENCES↗

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fatigue behavior and life prediction of a SiC/Ti-24Al-11Nb composite under isothermal conditions

Metal Matrix Composites (MMC) and Intermetallic Matrix Composites (IMC) were identified as potential material candidates for advanced aerospace applications. They are especially attractive for high temperature applications which require a low density material that maintains its structural integrity at elevated temperatures. High temperature fatigue resistance plays an important role in determining the structural integrity of the material. This study attempts to examine the relevance of test techniques, failure criterion, and life prediction as they pertain to an IMC material, specifically, unidirectional SiC fiber reinforced titanium aluminide. A series of strain and load controlled fatigue tests were conducted on unidirectional SiC/Ti-24Al-11Nb composite at 425 and 815 C. Several damage mechanism regimes were identified by using a strain-based representation of the data, Talreja's fatigue life diagram concept. Results of these tests were then used to address issues of test control modes, definition of failure, and testing techniques. Finally, a strain-based life prediction method was proposed for an IMC under tensile cyclic loadings at elevated temperatures.

Bartolotta, Paul A.↗

NASA Tech Briefs, January 2004

Topics covered include: Multisensor Instrument for Real-Time Biological Monitoring; Sensor for Monitoring Nanodevice-Fabrication Plasmas; Backed Bending Actuator; Compact Optoelectronic Compass; Micro Sun Sensor for Spacecraft; Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets; Finned-Ladder Slow-Wave Circuit for a TWT; Directional Radio-Frequency Identification Tag Reader; Integrated Solar-Energy-Harvesting and -Storage Device; Event-Driven Random-Access-Windowing CCD Imaging System; Stroboscope Controller for Imaging Helicopter Rotors; Software for Checking State-charts; Program Predicts Broadband Noise from a Turbofan Engine; Protocol for a Delay-Tolerant Data-Communication Network; Software Implements a Space-Mission File-Transfer Protocol; Making Carbon-Nanotube Arrays Using Block Copolymers: Part 2; Modular Rake of Pitot Probes; Preloading To Accelerate Slow-Crack-Growth Testing; Miniature Blimps for Surveillance and Collection of Samples; Hybrid Automotive Engine Using Ethanol-Burning Miller Cycle; Fabricating Blazed Diffraction Gratings by X-Ray Lithography; Freeze-Tolerant Condensers; The StarLight Space Interferometer; Champagne Heat Pump; Controllable Sonar Lenses and Prisms Based on ERFs; Measuring Gravitation Using Polarization Spectroscopy; Serial-Turbo-Trellis-Coded Modulation with Rate-1 Inner Code; Enhanced Software for Scheduling Space-Shuttle Processing; Bayesian-Augmented Identification of Stars in a Narrow View; Spacecraft Orbits for Earth/Mars-Lander Radio Relay; and Self-Inflatable/Self-Rigidizable Reflectarray Antenna.

Source record↗

Verification of Coupled Hydraulic Fracturing Simulators Using Laboratory-Scale Experiments

In this work, we aim to verify the predictions of the numerical simulators, which are used for designing field-scale hydraulic stimulation experiments. Although a strong theoretical understanding of this process has been gained over the past few decades, numerical predictions of fracture propagation in low-permeability rocks still remains a challenge. Against this background, we performed controlled laboratory-scale hydraulic fracturing experiments in granite samples, which not only provides high-quality experimental data but also a well-characterized experimental set-up. Using the experimental pressure responses and the final fracture sizes as benchmark, we compared the numerical predictions of two coupled hydraulic fracturing simulators—CSMP and GEOS. Both the simulators reproduced the experimental pressure behavior by implementing the physics of Linear Elastic Fracture Mechanics (LEFM) and lubrication theory within a reasonable degree of accuracy. The simulation results indicate that even in the very low-porosity (1–2 %) and low-permeability (10 -18 m 2 - 10 -19 m 2 ) crystalline rocks, which are usually the target of EGS, fluid-loss into the matrix and unsaturated flow impacts the formation breakdown pressure and the post-breakdown pressure trends. Therefore, underestimation of such parameters in numerical modeling can lead to significant underestimation of breakdown pressure. The simulation results also indicate the importance of implementing wellbore solvers for considering the effect of system compressibility and pressure drop due to friction in the injection line. The varying injection rate as a result of decompression at the instant of fracture initiation affects the fracture size, while the entry friction at the connection between the well and the initial notch may cause an increase in the measured breakdown pressure.

15 GEOTHERMAL ENERGY↗