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NASA NTRS1961

Direct Measurements of Interplanetary Dust Particles in the Vicinity of Earth

The direct measurements made by the Explorer VIII satellite provide the first sound basis for analyzing all available direct measurements of the distribution of interplanetary dust particles. The model average distribution curve established by such an analysis departs significantly from that predicted by the (uncertain) extrapolation of results from meteor observations. A consequence of this difference is that the daily accretion of interplanetary particulate matter by the earth is now considered to be mainly dust particles of the direct measurements range of particle size. Almost all the available direct measurements obtained with microphone systems on rockets, satellites, and spacecraft fit directly on the distribution curve defined by Explorer VIII data. The lack of reliable datum points departing significantly from the model average distribution curve means that available direct measurements show no discernible evidence of an appreciable geocentric concentration of interplanetary dust particles.

McCracken, C. W.↗

NASA NTRS2014

Adaptive Controller Effects on Pilot Behavior

Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

Trujillo, Anna C.↗

NASA NTRS2017

Aeroelastic Uncertainty Quantification Studies Using the S4T Wind Tunnel Model

This paper originates from the joint efforts of an aeroelastic study team in the Applied Vehicle Technology Panel from NATO Science and Technology Organization, with the Task Group number AVT-191, titled "Application of Sensitivity Analysis and Uncertainty Quantification to Military Vehicle Design." We present aeroelastic uncertainty quantification studies using the SemiSpan Supersonic Transport wind tunnel model at the NASA Langley Research Center. The aeroelastic study team decided treat both structural and aerodynamic input parameters as uncertain and represent them as samples drawn from statistical distributions, propagating them through aeroelastic analysis frameworks. Uncertainty quantification processes require many function evaluations to asses the impact of variations in numerous parameters on the vehicle characteristics, rapidly increasing the computational time requirement relative to that required to assess a system deterministically. The increased computational time is particularly prohibitive if high-fidelity analyses are employed. As a remedy, the Istanbul Technical University team employed an Euler solver in an aeroelastic analysis framework, and implemented reduced order modeling with Polynomial Chaos Expansion and Proper Orthogonal Decomposition to perform the uncertainty propagation. The NASA team chose to reduce the prohibitive computational time by employing linear solution processes. The NASA team also focused on determining input sample distributions.

Nikbay, Melike↗

DOE OSTI2025

Bidding Curve Design for Hybrid Power Plants with Uncertain Solar Forecast

This paper presents a novel bidding curve design algorithm tailored for hybrid power plants (HPPs) to participate in the wholesale electricity market. Utilizing forecasts for photovoltaic (PV) generation and available battery power, our algorithm strategically computes the bidding curve to maximize HPP profit while adeptly managing the inherent uncertainty associated with PV power generation. In addition, the introduction of the penalty cost in HPP bidding curves provides the system operator a tool to effectively manage the system-level uncertainty that caused by HPPs. Numerical analysis through Monte Carlo simulations confirms that our bidding curve methodology outperforms the benchmark across various scenarios.

bidding curve↗

DOE OSTI2021

Assessing Adaptive Irrigation Impacts on Water Scarcity in Nonstationary Environments—A Multi‐Agent Reinforcement Learning Approach

Abstract One major challenge in water resource management is to balance the uncertain and nonstationary water demands and supplies caused by the changing anthropogenic and hydroclimate conditions. To address this issue, we developed a reinforcement learning agent‐based modeling (RL‐ABM) framework where agents (agriculture water users) are able to learn and adjust water demands based on their interactions with the water systems. The intelligent agents are created by a reinforcement learning algorithm adapted from the Q‐learning algorithm. We illustrated this framework in a case study where the RL‐ABM is two‐way coupled with the Colorado River Simulation System (CRSS), a long‐term planning model used for the administration of the Colorado River Basin, for assessing agriculture water uses impacts on water scarcity. Seventy‐eight intelligent agents are simulated, which can be grouped into three categories based on their parameter values: the “aggressive” (swift actions; low regrets), the “forward‐looking conservative” (mild actions; high regrets; fast learning), and the “myopic conservative” (mild actions; median regrets; slow learning). The ABM‐CRSS results showed that the major reservoirs in the Upper Colorado Basin might experience more frequent water shortages due to the increasing water uses compared to the original CRSS results. If the drought continues, the case study also demonstrates that agents can learn and adjust their demands.

Hung, Fengwei↗

DOE OSTI2024

Characterizing the multisectoral impacts of future global hydrologic variability

There is significant uncertainty in how global water supply will evolve in the future, due to uncertain climate, socioeconomic, and land use change drivers and variability of hydrologic processes. It is critical to characterize the potential impacts of uncertainty in future water supply given its importance for food and energy production. In this work, we introduce a framework that integrates stochastic hydrology and human-environmental systems to characterize uncertainty in future water supply and its multisector impacts. We develop a global stochastic watershed model and demonstrate that this model can generate a large ensemble of realizations of basin-scale runoff with global coverage that preserves the mean, variance, and spatial correlation of a historical benchmark. We couple this model with a well-known human-environmental systems model to explore the impacts of runoff variability on the water and agricultural sectors across spatial scales. We find that the impacts of future hydrologic variability vary across sectors and regions. Impacts are felt most strongly in the water and agricultural sectors for basins that are expected to have unsustainable water use in the future, such as the Indus River basin. For this basin, we find that the variability in future irrigation water withdrawals and irrigated cropland increase over time due to uncertainty in renewable water supply. We also use the Indus basin to show how our stochastic ensemble can be leveraged to explore the global multisector consequences of local extreme runoff conditions. This work introduces a novel technique to explore the propagation of future hydrologic variability across human and natural systems and spatial scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Observations of Binary Stars with the Differential Speckle Survey Instrument. IX. Observations of Known and Suspected Binaries, and a Partial Survey of Be Stars

We report 370 measures of 170 components of binary and multiple-star systems, obtained from speckle imaging observations made with the Differential Speckle Survey Instrument at Lowell Observatory’s Discovery Channel Telescope in 2015 through 2017. Of the systems studied, 147 are binary stars, 10 are seen as triple systems, and 1 quadruple system is measured. Seventy-six high-quality nondetections and 15 newly resolved components are presented in our observations. The uncertainty in relative astrometry appears to be similar to our previous work at Lowell, namely, linear measurement uncertainties of approximately 2 mas, and the relative photometry appears to be uncertain at the 0.1–0.15 mag level. Using these measures and those in the literature, we calculate six new visual orbits, including one for the Be star 66 Oph and two combined spectroscopic–visual orbits. The latter two orbits, which are for HD 22451 (YSC 127) and HD 185501 (YSC 135), yield individual masses of the components at the level of 2% or better, and independent distance measures that in one case agrees with the value found in the Gaia DR2 and in the other disagrees at the 2σ level. We find that HD 22451 consists of an F6V+F7V pair with orbital period of 2401.1 ± 3.2 days and masses of 1.342 ± 0.029 and 1.236±0.026 M{sub ⊙}. For HD 185501, both stars are G5 dwarfs that orbit one another with a period of 433.94 ± 0.15 days, and the masses are 0.898 ± 0.012 and 0.876±0.012 M{sub ⊙}. We discuss the details of both the new discoveries and the orbit objects.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Organic carbon burial by river meandering partially offsets bank erosion carbon fluxes in a discontinuous permafrost floodplain

Abstract. Arctic river systems erode permafrost in their banks and mobilize particulate organic carbon (OC). Meandering rivers can entrain particulate OC from permafrost many meters below the depth of annual thaw, potentially enabling the production of greenhouse gases. However, the amount and fate of permafrost OC that is mobilized by river erosion is uncertain. To constrain OC fluxes due to riverbank erosion and deposition, we collected riverbank and floodplain sediment samples along the Koyukuk River, which meanders through discontinuous permafrost in the Yukon River watershed, Alaska, USA, with an average migration rate of 0.52 m yr−1. We measured sediment total OC (TOC) content, radiocarbon activity, water content, bulk density, grain size, and floodplain stratigraphy. Radiocarbon activity and TOC content were higher in samples dominated by silt as compared to sand, which we used to map OC content onto floodplain stratigraphy and estimate carbon fluxes due to river meandering. Results showed that the Koyukuk River erodes and re-deposits a substantial flux of OC each year due to its depth and high migration rate, generating a combined OC flux of a similar magnitude to the floodplain net ecological productivity. However, sediment being eroded from cutbanks and deposited as point bars had similar OC stocks (mean ± 1 SD of 125.3±13.1 kg OC m−2 in cutbanks versus 114.0±15.7 kg OC m−2 in point bars) whether or not the banks contained permafrost. We also observed radiocarbon-depleted biospheric OC in both cutbanks and permafrost-free point bars. These results indicate that a substantial fraction of aged biospheric OC that is liberated from floodplains by bank erosion is subsequently re-deposited in point bars rather than being oxidized. The process of aging, erosion, and re-deposition of floodplain organic material may be intrinsic to river–floodplain dynamics, regardless of permafrost content.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2008

Science Goals in Radiation Protection for Exploration

Space radiation presents major challenges to future missions to the Earth s moon or Mars. Health risks of concern include cancer, degenerative and performance risks to the central nervous system, heart and lens, and the acute radiation syndromes. The galactic cosmic rays (GCR) contain high energy and charge (HZE) nuclei, which have been shown to cause qualitatively distinct biological damage compared to terresterial radiation, such as X-rays or gamma-rays, causing risk estimates to be highly uncertain. The biological effects of solar particle events (SPE) are similar to terresterial radiation except for their biological dose-rate modifiers; however the onset and size of SPEs are difficult to predict. The high energies of GCR reduce the effectiveness of shielding, while SPE s can be shielded however the current gap in radiobiological knowledge hinders optimization. Methods used to project risks on Earth must be modified because of the large uncertainties in projecting health risks from space radiation, and thus impact mission requirements and costs. We describe NASA s unique approach to radiation safety that applies probabilistic risk assessments and uncertainty based criteria within the occupational health program for astronauts and to mission design. The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in radiation risk projection models. Exploration science goals in radiation protection are centered on ground-based research to achieve the necessary biological knowledge, and in the development of new technologies to improve SPE monitoring and optimize shielding. Radiobiology research is centered on a ground based program investigating the radiobiology of high-energy protons and HZE nuclei at the NASA Space Radiation Laboratory (NSRL) located at DoE s Brookhaven National Laboratory in Upton, NY. We describe recent NSRL results that are closing the knowledge gap in HZE radiobiology and improving exploration risk estimates. Linking probabilistic risk assessment to research goals makes it possible to express risk management objectives in terms of quantitative metrics, which include the number of days in space without exceeding a given risk level within well defined confidence limits, and probabilistic assessments of the effectiveness of design trade spaces such as material type, mass, solar cycle, crew selection criteria, and biological countermeasures. New research in SPE alert and risk assessment, individual radiation sensitivity, and biological countermeasure development are described.

Cucinotta, Francs A.↗

DOE OSTI2024

Bidding Curve Design for Hybrid Power Plants with Uncertain Solar Forecast: Preprint

bidding curve↗

DOE OSTI2022

The Source Permeator System and Tritium Transport in the TEX PbLi Loop

In this work, permeation is investigated for the introduction of hydrogen isotopes into PbLi for the Tritium Extraction eXperiment (TEX). TEX is a forced-convection PbLi loop under construction at Idaho National Laboratory (INL) that will test the vacuum permeator (VP) method of tritium extraction from PbLi. The source permeator (SP) delivers atomic hydrogen (H, D, and T) from a gas-phase reservoir into the PbLi via a permeable dense metal membrane. A modular and a fixed source permeator system are presented. In the modular design, PbLi flows through the inside of a tubular membrane and gas-phase hydrogen is introduced on the outside of the membrane. Atomic hydrogen permeates radially inward through the membrane into the PbLi. In the fixed design, PbLi flows into an expansion chamber with closed-ended tubular membranes inserted. Gas-phase hydrogen is introduced on the inside of the closed-ended membranes and atomic hydrogen permeates radially outward into the flowing PbLi. Hydrogen-transport models based on steady-state mass transport through PbLi and permeation through the metal membrane were developed to assess the operation of the source permeator relative to experimental variables and to allow understanding of uncertain parameter effects, such as PbLi hydrogen-transport properties and the effective hydrogen permeability of the vacuum permeator. This modeling effort considers iron as the source permeator material and vanadium as the vacuum permeator material.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Artificial intelligence for materials research at extremes

Abstract Materials development is slow and expensive, taking decades from inception to fielding. For materials research at extremes, the situation is even more demanding, as the desired property combinations such as strength and oxidation resistance can have complex interactions. Here, we explore the role of AI and autonomous experimentation (AE) in the process of understanding and developing materials for extreme and coupled environments. AI is important in understanding materials under extremes due to the highly demanding and unique cases these environments represent. Materials are pushed to their limits in ways that, for example, equilibrium phase diagrams cannot describe. Often, multiple physical phenomena compete to determine the material response. Further, validation is often difficult or impossible. AI can help bridge these gaps, providing heuristic but valuable links between materials properties and performance under extreme conditions. We explore the potential advantages of AE along with decision strategies. In particular, we consider the problem of deciding between low-fidelity, inexpensive experiments and high-fidelity, expensive experiments. The cost of experiments is described in terms of the speed and throughput of automated experiments, contrasted with the human resources needed to execute manual experiments. We also consider the cost and benefits of modeling and simulation to further materials understanding, along with characterization of materials under extreme environments in the AE loop. Graphical abstract AI sequential decision-making methods for materials research: Active learning, which focuses on exploration by sampling uncertain regions, Bayesian and bandit optimization as well as reinforcement learning (RL), which trades off exploration of uncertain regions with exploitation of optimum function value. Bayesian and bandit optimization focus on finding the optimal value of the function at each step or cumulatively over the entire steps, respectively, whereas RL considers cumulative value of the labeling function, where the latter can change depending on the state of the system (blue, orange, or green).

36 MATERIALS SCIENCE↗

NASA NTRS2016

Attitude Control System Design for CubeSats Configured with Exo-Brake Parachute

This paper develops a novel attitude control strategy for an Earth orbiting CubeSat spacecraft by utilizing the exo-brake parachute to modulate the atmospheric drag forces as a source of attitude control authority, enabling orbital exo-sail maneuvers. In particular, the spacecraft attitude controls can be realized through the two dimensional exo-sail maneuvers in pitch and yaw directions. The uncertain atmospheric drag induced disturbance torque is estimated through an adaptive parameter estimation process which makes use of the adaptive least-squares minimization techniques. The covariance updating law with a variable forgetting factor is adopted and it can be shown that the convergent rate for the estimation errors can be chosen at the same level as the forgetting factor, in order to meet the design needs. The proposed approach is best suited for Earth orbiting micronano-satellite applications, which are configured with exo-brake parachute. With integration of exo-sail actuation mechanism and disturbance estimation, we demonstrate through simulations that exo-sail induced control torque for CubeSat attitude maneuver is feasible.

Disturbance estimation↗

NASA NTRS1996

Computational modeling of magnetically actuated propellant orientation

Unlike terrestrial applications where gravity positions liquid at the 'bottom' of the tank, the location of liquid propellant in spacecraft tanks is uncertain unless specific actions are taken or special features are built into the tank. Some mission events require knowledge of liquid position prior to a particular action: liquid must be positioned over the tank outlet prior to starting the main engines and must be moved away from the tank vent before vapor can be released overboard to reduce pressure. It may also be desirable to positively position liquid to improve propulsion system performance: moving liquid away from the tank walls will dramatically decrease the rate of heat transfer to the propellant, suppressing the boil-off rate, thereby reducing overall mission propellant requirements. The process of moving propellant to a desired position is referred to as propellant orientation or reorientation. Several techniques have been developed to positively position propellant in spacecraft tanks and each technique imposes additional requirements on vehicle design. Propulsive reorientation relies on small auxiliary thrusters to accelerate the tank. The inertia of the liquid causes it to collect in the aft-end of the tank if the acceleration is forward. This technique requires that additional thrusters be added to the vehicle, that additional propellant be carried in the vehicle, and that an additional operational maneuver be executed. Another technique uses Liquid Acquisition Devices (LAD's) to positively position propellants. These devices rely on surface tension to hold the liquid within special geometries (i.e. vanes, wire-mesh channels, start-baskets). While avoiding some of the penalties of propulsive orientation, this technique requires the addition of complicated hardware inside the propellant tank and performance for long duration missions is uncertain. The subject of the present research is an alternate technique for positively positioning liquid within spacecraft propellant tanks: magnetic fields.

Hochstein, John I.↗

DOE OSTI2020

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1990

Task directed sensing

High-level robot control research must confront the limitations imposed by real sensors if robots are to be controlled effectively in the real world. In particular, sensor limitations make it impossible to maintain a complete, detailed world model of the situation surrounding the robot. To address the problems involved in planning with the resulting incomplete and uncertain world models, traditional robot control architectures must be altered significantly. Task-directed sensing and control is suggested as a way of coping with world model limitations by focusing sensing and analysis resources on only those parts of the world relevant to the robot's active goals. The RAP adaptive execution system is used as an example of a control architecture designed to deploy sensing resources in this way to accomplish both action and knowledge goals.

Firby, R. James↗

NASA NTRS2007

Importance of Rain Evaporation and Continental Convection in the Tropical Water Cycle

Atmospheric moisture cycling is an important aspect of the Earth's climate system, yet the processes determining atmospheric humidity are poorly understood. For example, direct evaporation of rain contributes significantly to the heat and moisture budgets of clouds, but few observations of these processes are available. Similarly, the relative contributions to atmospheric moisture over land from local evaporation and humidity from oceanic sources are uncertain. Lighter isotopes of water vapour preferentially evaporate whereas heavier isotopes preferentially condense and the isotopic composition of ocean water is known. Here we use this information combined with global measurements of the isotopic composition of tropospheric water vapour from the Tropospheric Emission Spectrometer (TES) aboard the Aura spacecraft, to investigate aspects of the atmospheric hydrological cycle that are not well constrained by observations of precipitation or atmospheric vapour content. Our measurements of the isotopic composition of water vapour near tropical clouds suggest that rainfall evaporation contributes significantly to lower troposphere humidity, with typically 20% and up to 50% of rainfall evaporating near convective clouds. Over the tropical continents the isotopic signature of tropospheric water vapour differs significantly from that of precipitation, suggesting that convection of vapour from both oceanic sources and evapotranspiration are the dominant moisture sources. Our measurements allow an assessment of the intensity of the present hydrological cycle and will help identify any future changes as they occur.

Worden, John↗

NASA NTRS2010

Formal Verification of Safety Buffers for Sate-Based Conflict Detection and Resolution

The information provided by global positioning systems is never totally exact, and there are always errors when measuring position and velocity of moving objects such as aircraft. This paper studies the effects of these errors in the actual separation of aircraft in the context of state-based conflict detection and resolution. Assuming that the state information is uncertain but that bounds on the errors are known, this paper provides an analytical definition of a safety buffer and sufficient conditions under which this buffer guarantees that actual conflicts are detected and solved. The results are presented as theorems, which were formally proven using a mechanical theorem prover.

Herencia-Zapana, Heber↗