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NASA NTRS2010

Correlation of Wissler Human Thermal Model Blood Flow and Shiver Algorithms

The Wissler Human Thermal Model (WHTM) is a thermal math model of the human body that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. The model has been shown to predict core temperature and skin temperatures higher and lower, respectively, than in tests of subjects in crew escape suit working in a controlled hot environments. Conversely the model predicts core temperature and skin temperatures lower and higher, respectively, than in tests of lightly clad subjects immersed in cold water conditions. The blood flow algorithms of the model has been investigated to allow for more and less flow, respectively, for the cold and hot case. These changes in the model have yielded better correlation of skin and core temperatures in the cold and hot cases. The algorithm for onset of shiver did not need to be modified to achieve good agreement in cold immersion simulations

Bue, Grant↗

NASA NTRSDate not supplied

Generalized Predictive Control for Active Stability Augmentation and Vibration Reduction on an Aeroelastic Tiltrotor Model

Tiltrotor aircraft are defining the state-of-the-art in vertical lift technology as they have the potential to greatly expand rotary-wing operational boundaries. However, they are often limited in forward flight speed due to complex coupled rotor and wing dynamic instabilities. The U.S. Army and NASA have been developing a new wind tunnel model, the TiltRotor Aeroelastic Stability Testbed(TRAST), to test proprotors in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) to investigate aeroelastic stability in cruise. The test is intended to provide high-quality research data for analytical tool development and validation. In addition, the TRAST model will support, develop, and mature new technologies for the design of advanced proprotor aircraft. Stability augmentation and vibration reduction during testing is planned with the use of an active control methodology known as Generalized Predictive Control(GPC). GPC is an autoregressive control law that experimentally acquires a system identification to derive the input-output relation of controls and corresponding sensors. This type of control law is especially useful for complex dynamic interactions that are difficult to explicitly model such as proprotor pylon instability, often referred to as whirl flutter. GPC has been successfully employed on other tiltrotor vehicles to suppress whirl flutter instabilities and vibrations. To aid in the characterization of the wind-tunnel model and in tool development, an analytical representation of the wind-tunnel model was developed using the rotorcraft comprehensive analysis system (RCAS) that simulates structural dynamics and aerodynamics. RCAS was used to derive state-space estimates of the physical plant at various flight conditions to test control law effectiveness. This paper will present an overview of the test article development, a description of RCAS, an explanation of the GPC methodology, and results of GPC being applied to state-space plant estimates of the TRAST model. In these simulations, GPC was effective at stabilizing the aircraft beyond the whirl-flutter boundary while simultaneously reducing vibrations across the flight regime. Additionally, a modern advancement to GPC, termed advanced GPC (AGPC), is introduced that enables a self-adapting system identification. Preliminary results show that AGPC is successful at self-correction as the plant changes from what was used for system identification.

tiltrotor↗

NASA NTRS1995

Looking around: 35 years of oculomotor modeling

Eye movements have attracted an unusually large number of researchers from many disparate fields, especially over the past 35 years. The lure of this system stemmed from its apparent simplicity of description, measurement, and analysis, as well as the promise of providing a "window in the mind." Investigators in areas ranging from biological control systems and neurological diagnosis to applications in advertising and flight simulation expected eye movements to provide clear indicators of what the sensory-motor system was accomplishing and what the brain found to be of interest. The parallels between compensatory eye movements and perception of spatial orientation have been a subject for active study in visual-vestibular interaction, where substantial knowledge has accumulated through experiments largely guided by the challenge of proving or disproving model predictions. Even though oculomotor control has arguably benefited more from systems theory than any other branch of motor control, many of the original goals remain largely unfulfilled. This paper considers some of the promising potential benefits of eye movement research and compares accomplishments with anticipated results. Four topics are considered in greater detail: (i) the definition of oculomotor system input and output, (ii) optimization of the eye movement system, (iii) the relationship between compensatory eye movements and spatial orientation through the "internal model," and (iv) the significance of eye movements as measured in (outer) space.

Flight Experiment↗

DOE OSTI2024

Forward and inverse predictive transient models of TREAT using surrogate reactivity models

In this work, we present two novel approaches for predicting the power evolution and control rod height of the Transient Reactor Test Facility (TREAT) to support experiment modeling; specifically, transient analysis of the NASA-sponsored Sirius series of experiments. These approaches utilize steady-state Monte Carlo model, point kinetics model, and surrogate models to predict power evolution and control rod axial position during transient experiments. Both approaches were tested and validated against several Sirius experiments that were performed in the TREAT facility at different power levels. The validation test results show very good agreement with the experimental data, and the models were able to accurately predict the power evolution and the axial control rod position with an average error within 3.0%. Finally, this indicates that these approaches will help the reactor engineering team of the TREAT facility in preparing and predicting the power and temperature of the experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2004

Theoretical Tools and Software for Modeling, Simulation and Control Design of Rocket Test Facilities

A rocket test stand and associated subsystems are complex devices whose operation requires that certain preparatory calculations be carried out before a test. In addition, real-time control calculations must be performed during the test, and further calculations are carried out after a test is completed. The latter may be required in order to evaluate if a particular test conformed to specifications. These calculations are used to set valve positions, pressure setpoints, control gains and other operating parameters so that a desired system behavior is obtained and the test can be successfully carried out. Currently, calculations are made in an ad-hoc fashion and involve trial-and-error procedures that may involve activating the system with the sole purpose of finding the correct parameter settings. The goals of this project are to develop mathematical models, control methodologies and associated simulation environments to provide a systematic and comprehensive prediction and real-time control capability. The models and controller designs are expected to be useful in two respects: 1) As a design tool, a model is the only way to determine the effects of design choices without building a prototype, which is, in the context of rocket test stands, impracticable; 2) As a prediction and tuning tool, a good model allows to set system parameters off-line, so that the expected system response conforms to specifications. This includes the setting of physical parameters, such as valve positions, and the configuration and tuning of any feedback controllers in the loop.

Richter, Hanz↗

DOE OSTI2026

Building Operation Model (Morpheus) for Dallas Fort Worth Airport (CRADA CRD-19-16301 Final Report)

The primary objective of this project was to leverage digital twin technology to enhance the design and operation of DFW Airport terminals and their associated energy systems. To achieve this, Morpheus, a building digital twin, was developed to guide improvements in airport operations, specifically targeting reductions in peak power demand and overall energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1998

Characterization and Design of Digital Pointing Subsystem for Optical Communication Demonstrator

The Optical Communications Demonstrator (OCD) is a laboratory-based lasercom demonstration terminal designed to validate several key technologies, including beacon acquisition, high bandwidth tracking, precision bearn pointing, and point-ahead compensation functions. It has been under active development over the past few years. The instrument uses a CCD array detector for both spatial acquisition and high-bandwidth tracking, and a fiber coupled laser transmitter. The array detector tracking concept provides wide field-of-view acquisition and permits effective platform jitter compensation and point-ahead control using only one steering mirror. This paper describes the detailed design and characterization of the digital control loop system which includes the Fast Steering Mirror (FSM), the CCD image tracker, and the associated electronics. The objective is to improve the overall system performance using laboratory measured data. The. design of the digital control loop is based on a linear time invariant open loop model. The closed loop performance is predicted using the theoretical model. With the digital filter programmed into the OCD control software, data is collected to verify the predictions. This paper presents the results of the, system modeling and performance analysis. It has been shown that measurement data closely matches theoretical predictions. An important part of the laser communication experiment is the ability of FSM to track the laser beacon within the. required tolerances. The pointing must be maintained to an accuracy that is much smaller than the transmit signal beamwidth. For an earth orbit distance, the system must be able to track the receiving station to within a few microradians. The failure. to do so will result in a severely degraded system performance.

Racho, C.↗

NASA NTRS2013

Effect of Residual Noncondensables on Pressurization and Pressure Control of a Zero-Boil-Off Tank in Microgravity

The Zero-Boil-Off Tank (ZBOT) Experiment is a small-scale experiment that uses a transparent ventless Dewar and a transparent simulant phase-change fluid to study sealed tank pressurization and pressure control with applications to on-surface and in-orbit storage of propellant cryogens. The experiment will be carried out under microgravity conditions aboard the International Space Station in the 2014 timeframe. This paper presents preliminary results from ZBOT's ground-based research that focuses on the effects of residual noncondensable gases in the ullage on both pressurization and pressure reduction trends in the sealed Dewar. Tank pressurization is accomplished through heating of the test cell wall in the wetted and un-wetted regions simultaneously or separately. Pressure control is established through mixing and destratification of the bulk liquid using a temperature controlled forced jet flow with different degrees of liquid jet subcooling. A Two-Dimensional axisymmetric two-phase CFD model for tank pressurization and pressure control is also presented. Numerical prediction of the model are compared to experimental 1g results to both validate the model and also indicate the effect of the noncondensable gas on evolution of pressure and temperature distributions in the ullage during pressurization and pressure control. Microgravity simulations case studies are also performed using the validated model to underscore and delineate the profound effect of the noncondensables on condensation rates and interfacial temperature distributions with serious implications for tank pressure control in reduced gravity.

Marangoni and Natural Convection↗

DOE OSTI2018

Tailoring Morphology of Cu–Ag Nanocrescents and Core–Shell Nanocrystals Guided by a Thermodynamic Model

The ability to predict and control the formation of bimetallic heterogeneous nanocrystals is desirable for many applications in plasmonics and catalysis. In this work, we observe the synthesis and characterization of stable, monodisperse, and solution-processed Cu-Ag bimetallic nanoparticles with specific but unusual elemental arrangements that are consistent with a recently developed thermodynamic model. Using air-free scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy, the distribution of Cu and Ag positions was unambiguously identified within individual nanocrystals (NCs), leading to the discovery of a Cu-Ag nanocrescent shape. A simple yet versatile thermodynamic model was applied to illustrate how the interplay between surface and interface energies determines the particle morphology. It is found that there exists a range of surface-to-interface energy ratios under which crescent-shaped nanocrystals are the thermodynamically favored products, with the morphology tunable by adjusting the Ag content. Moreover, we show the conversion of Cu-Ag nanocrescents into Ag@Cu 2 O upon mild oxidation, whereas fully core-shell Cu@Ag NCs are robust against oxidation up to 100 °C. The plasmonic and interband absorptions of Cu-Ag NCs depend on the composition and the degree of Cu oxidation, which may find application in light-driven catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1976

Correlation study of theoretical and experimental results for spin tests of a 1/10 scale radio control model

A correlation study was conducted to determine the ability of current analytical spin prediction techniques to predict the flight motions of a current fighter airplane configuration during the spin entry, the developed spin, and the spin recovery motions. The airplane math model used aerodynamics measured on an exact replica of the flight test model using conventional static and forced-oscillation wind-tunnel test techniques and a recently developed rotation-balance test apparatus capable of measuring aerodynamics under steady spinning conditions. An attempt was made to predict the flight motions measured during stall/spin flight testing of an unpowered, radio-controlled model designed to be a 1/10 scale, dynamically-scaled model of a current fighter configuration. Comparison of the predicted and measured flight motions show that while the post-stall and spin entry motions were not well-predicted, the developed spinning motion (a steady flat spin) and the initial phases of the spin recovery motion are reasonably well predicted.

Bihrle, W., Jr.↗

DOE OSTI2014

Signatures for Mass Spectrometry Data Quality

Not Available

Amidan, Brett G.↗

DOE OSTI2015

An Efficient Silent Data Corruption Detection Method with Error-Feedback Control and Even Sampling for HPC Applications

The silent data corruption (SDC) problem is attracting more and more attentions because it is expected to have a great impact on exascale HPC applications. SDC faults are hazardous in that they pass unnoticed by hardware and can lead to wrong computation results. In this work, we formulate SDC detection as a runtime one-step-ahead prediction method, leveraging multiple linear prediction methods in order to improve the detection results. The contributions are twofold: (1) we propose an error feedback control model that can reduce the prediction errors for different linear prediction methods, and (2) we propose a spatial-data-based even-sampling method to minimize the detection overheads (including memory and computation cost). We implement our algorithms in the fault tolerance interface, a fault tolerance library with multiple checkpoint levels, such that users can conveniently protect their HPC applications against both SDC errors and fail-stop errors. We evaluate our approach by using large-scale traces from well-known, large-scale HPC applications, as well as by running those HPC applications on a real cluster environment. Experiments show that our error feedback control model can improve detection sensitivity by 34-189% for bit-flip memory errors injected with the bit positions in the range [20,30], without any degradation on detection accuracy. Furthermore, memory size can be reduced by 33% with our spatial-data even-sampling method, with only a slight and graceful degradation in the detection sensitivity.

Di, Sheng↗

DOE OSTI2020

A Machine Learning-based Approach to Predict the Aggregate Flexibility of HVAC Systems

Use of renewable energy resources can play a significant role in mitigation of climate change since they reduce the dependency on fossil fuels. However, high penetration of renewable energy resources into the power grid may cause some reliability problems. Ancillary services are key to realize the potential of renewable resources without disturbing the grid reliability. In recent years, many control approaches focused on exploiting the aggregate flexible heating, ventilation, and air-conditioning (HVAC) loads of buildings. However, there are still research gaps in assessing in advance the resulting indoor temperature responses for given total power and weather profiles before implementing the controls in the buildings. Such an assessment is critical to guarantee satisfying both the grid related objective (reliability) and the building related objective (occupants' comfort). Towards addressing this research gap, this paper presents a machine-learning approach for predicting the ratings of indoor temperature responses. In this approach, a prediction model was developed using a dataset generated by a set of model-free control simulations. The developed model achieved high prediction accuracy and showed the potential of the proposed approach.

Amasyali, Kadir↗

DOE OSTI2013

A TCP model for external beam treatment of intermediate-risk prostate cancer

Purpose: Biological models offer the ability to predict clinical outcomes. The authors describe a model to predict the clinical response of intermediate-risk prostate cancer to external beam radiotherapy for a variety of fractionation regimes. Methods: A fully heterogeneous population averaged tumor control probability model was fit to clinical outcome data for hyper, standard, and hypofractionated treatments. The tumor control probability model was then employed to predict the clinical outcome of extreme hypofractionation regimes, as utilized in stereotactic body radiotherapy. Results: The tumor control probability model achieves an excellent level of fit, R{sup 2} value of 0.93 and a root mean squared error of 1.31%, to the clinical outcome data for hyper, standard, and hypofractionated treatments using realistic values for biological input parameters. Residuals Less-Than-Or-Slanted-Equal-To 1.0% are produced by the tumor control probability model when compared to clinical outcome data for stereotactic body radiotherapy. Conclusions: The authors conclude that this tumor control probability model, used with the optimized radiosensitivity values obtained from the fit, is an appropriate mechanistic model for the analysis and evaluation of external beam RT plans with regard to tumor control for these clinical conditions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics

Abstract. African and South American (ASA) wildfires account for more than 70 % of global burned areas and have strong connection to local climate for sub-seasonal to seasonal wildfire dynamics. However, representation of the wildfire–climate relationship remains challenging due to spatiotemporally heterogenous responses of wildfires to climate variability and human influences. Here, we developed an interpretable machine learning (ML) fire model (AttentionFire_v1.0) to resolve the complex controls of climate and human activities on burned areas and to better predict burned areas over ASA regions. Our ML fire model substantially improved predictability of burned areas for both spatial and temporal dynamics compared with five commonly used machine learning models. More importantly, the model revealed strong time-lagged control from climate wetness on the burned areas. The model also predicted that, under a high-emission future climate scenario, the recently observed declines in burned area will reverse in South America in the near future due to climate changes. Our study provides a reliable and interpretable fire model and highlights the importance of lagged wildfire–climate relationships in historical and future predictions.

58 GEOSCIENCES↗

DOE OSTI2020

High Temperature Erosion Modeling in Particle Based CSP Systems

1. Introduction. Wear and erosion damage of materials from solid particle and surface interactions is a major issue in various industries. Although more common in mining and oil and gas production, erosion is becoming a critical issue in renewable technologies as well such as particle based concentrated solar thermal power (CSP) systems. In particle based CSP systems, solid particles are used to absorb solar energy and as thermal storage. However, these particles may cause significant amount of wear to system components while through the system at high temperatures. This damage can be costly, and therefore, requires a greater understanding of solid particle erosion in CSP systems. Throughout the years, models and tools have been developed to predict and control erosion in industries such as oil and gas production. However, these erosion models and erosion prediction tools have been mainly developed based on erosion data for much higher velocities and lower temperatures, i.e. the operating conditions for which the existing models have been built are not pertinent to those expected in CSP system. It is known that erosion depends on many factors such as material properties, erodent particle properties, and particle impact speed and angle. However, the effect of temperature on erosion is not vastly investigated. In this work, a temperature-based correlation is introduced that will be used to modify the existing erosion models to predict erosion rates at velocities and temperatures relevant to Gen3 CSP systems. The existing models are first validated against erosion experiments run at low temperatures and low velocities. Subsequently, a temperature correction term is developed that can extend the existing models to high temperatures, based on the available experimental data showing the effect of temperature on impact erosion. 2. Erosion Models. Continuing sequence of impacts from solid particles on surfaces would result in loss of material due to mechanical interaction between solid surface and particles. Erosion equations have been developed to predict erosion under different conditions and erosion mechanism, including cutting and deformation erosion. These models are mainly either mechanistic, empirical, and semi-mechanistic models, when the latter combine the theory of the erosion mechanism and particle motion with the available experimental data. One of the first empirical correlation was introduced by American Petroleum Institute (API) Recommended Practice (RP) 14E [1]. This correlation was very conservative, and several improved empirical and semi-mechanistic equations were developed in the years following. More recently, the models introduced by Erosion/Corrosion Research Center (E/CRC) at the University of Tulsa and Arabnejad. et al. [2] are frequently used in the literature and industry, as they account for many parameters affecting erosion including particle impact speed and angle, material density and hardness, and particle size and shape. However, both these models were developed based on data at relatively high velocities and also do not take into account any mechanical changes in material associated with thermal cycling at high temperatures. 3. Erosion Prediction at High Temperatures. In this work, the accuracy of Arabnejad et al. model and E/CRC model is investigated to predict impact erosion at conditions relevant to Gen3 CSP systems. Two significant deviations expected in Gen3 systems compared to operating conditions used to build these models are particle impact velocities and system temperature. As a first step, the performance of these models was validated at low velocities and temperatures. Impact erosion experiments were conducted on SS316 coupons using HSP 40/70 ceramic particles. Assuming particle rate of 1 kg/s/m, 0.0254 m of particle curtain thickness, and particle velocity of 1.5 m/s in the system, an overall erosion of 0.59 mm/year was calculated. The experimental results were subsequently compared to those from computational simulations and erosion of 0.47 mm/year was obtained using the Arabnejad et al. model. The results indicated that the models work well at low velocities and low temperature conditions. To account for temperature effect, a mathematical correlation was developed using data published by DUCOM [3] for Inconel 600 eroded by alumina particles at high velocities. The correlation was applied to both Arabnejad et. al model and the E/CRC model. The prediction results from these modified models were within 20% of this experimental data. Predictions of of erosion by the modified E/CRC model at three different temperatures are made. Similar to the calculation at low temperature, a typical CSP system with 1 kg/s/m of particle flow rate per unit length of the particle curtain and a curtain thickness of 0.0254 m is assumed. The annual thickness loss calculations were run for different particle impact velocities, assuming a uniform particle impact area equal to the cross-sectional area of the curtain (particle-particle interactions and dispersion of particles are not considered in obtaining the results). It is observed that erosion increases exponentially as temperature increases. Furthermore, it is also noted that, erosion changes non-linearly with impact velocity. Currently, experiments are also being conducted to measure erosion of SS316 at 800 ºC with HSP 40/70 particles at low impact velocities. We expect to use the results from high temperature testing to further improve the temperature correlation function. Similar models are also being developed for abrasion erosion resulting from particle sliding along the surfaces as well as attrition from particle to particle and particle to surface interactions. References. [1] Institute, A. P. (1991). API Recommended Practice for Design and Installation of Offshore Production Platform Piping System, API RP 14E. [2] Arabnejad, H., Mansouri, A., Shirazi, S. A., and McLaury, B. S. (2015a). Development of mechanistic erosion equation for solid particles. Wear, 332–333, 1044–1050. http://doi.org/10.1016/j.wear.2015.01.031. [3] https://ducom.com/high-temperature-erosion-evaluating-sample-wear/

14 SOLAR ENERGY↗

NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

route advisories↗

NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

operational acceptability↗