MALA-within-Gibbs Samplers for High-Dimensional Distributions with Sparse Conditional Structure
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Mathematics↗
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A study of power conditioning and power distribution and components
A comprehensive simulation and analysis performed on the operation of the regulator part of the Charger/Battery/Regulator Module (CBRM) are detailed. The CBRM is utilized as an integral component of the Skylab/Apollo Telescope Mount (ATM) electrical power system and contains a switching mode electronic regulator. Implementing circuit analysis techniques, pertinent voltages and currents are calculated; these, in turn, are incorporated into the regulator system study. Investigation of the turn-on and turn-off times associated with the switching circuitry is performed and an examination is made on these calculations. A simulation model computer program is utilized to generate graphs that relate various CBRM parameters to one another.
Horton, H. M.↗
A modular Space Station/Base electrical power system - Requirements and design study.
The requirements and procedures necessary for definition and specification of an electrical power system (EPS) for the future space station are discussed herein. The considered space station EPS consists of a replaceable main power module with self-contained auxiliary power, guidance, control, and communication subsystems. This independent power source may 'plug into' a space station module which has its own electrical distribution, control, power conditioning, and auxiliary power subsystems. Integration problems are discussed, and a transmission system selected with local floor-by-floor power conditioning and distribution in the station module. This technique eliminates the need for an immediate long range decision on the ultimate space base power sources by providing capability for almost any currently considered option.
Eliason, J. T.↗
Rain cell size statistics derived from radar observations at Wallops Island, Virginia
An investigation of two-dimensional rain cell size statistics has analyzed regression relations relating radar-determined rain rates to disdrometer data. This has yielded least-squares fits of radar reflectivity factors, and the application of a contouring program has generated 22,000 contours in which each isopleth belongs to predefined rain-rate intervals. An abundance of total and cell contours were observed belonging to all rain-rate categories. Both the computed number distributions and the conditional cumulative distributions as a function of contour diameter were found to be represented with good approximation by given exponential functions.
Goldhirsh, J.↗
HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR
Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.
79 ASTRONOMY AND ASTROPHYSICS↗
Conditional Probability And The Sparse Distributed Memory
Report presents conditional-probability interpretation of Kanerva's sparse distributed memory (SDM). SDM is conceptual digital electronic memory in which addresses chosen sparsely in space of many dimensions and content of memory at each address positive or negative integer written (incremented or decremented) or read according to special rules. Contents of SDM constitute Monte Carlo approximation to multidimensional conditional-probability integral.
Anderson, Charles H.↗
Optimal Operation of Soft Open Points in Active Distribution Networks Under Three-Phase Unbalanced Conditions
The asymmetric integration of distributed generators (DGs) exacerbates the three-phase unbalanced condition in distribution systems. The serious unbalanced operation causes inefficient utilization of network assets and security risks in the system. Soft open point (SOP) is a flexible power electronic device which can achieve accurate active and reactive power flow control to balance the power flow among phases. This paper proposes an SOPs-based operation strategy for unbalanced active distribution networks (ADNs). By regulating the operation of SOPs, the strategy can reduce power losses and simultaneously mitigate the three-phase unbalance of the upper-level grid. Semidefinite programming (SDP) relaxation is advocated to convert the original non-convex, nonlinear optimization model into an SDP formulation, which can be efficiently solved to meet the requirement of rapid adjustment. Case studies are conducted on the modified IEEE 33-node and IEEE 123-node distribution system to verify the effectiveness and efficiency of the proposed strategy.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas
Estimation of daily suspended sediment concentration (SSC) is required for water resources and environment management. In this paper, a copula-based stochastic method was proposed for daily SSC simulation. Here, the multivariate copula function, constructed based on a bivariate copula and two bivariate conditional probability distributions, was used to model the temporal and cross dependence structures in daily SSCs. Then, the daily SSCs were generated by sampling from the multivariate conditional distribution. As a result, synthetic long-term SSCs data beyond the limited observation period can be provided for water resources managers, which plays a critical role in accurately estimating frequency and magnitude of extreme SSCs events. The proposed method was under rigorous examination by applying to a case study at Pingshan station in the Jinsha River Basin, China. Results showed that the generated daily SSC sequences not only had a high degree of accuracy in preserving the statistical characteristics of the daily SSC observations, but also captured both the temporal correlation and the cross-correlation between the daily streamflow and daily SSC. Specifically, the average daily relative error values corresponding to mean, standard deviation, skewness, lag-1 temporal correlation, and cross correlation were 0.87%, 4.24%, 7.52%, 0.51% and 2.02%, respectively. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resources management such as frequency analysis and risk assessment of extreme SSC events.
54 ENVIRONMENTAL SCIENCES↗
Ventenata dubia projected to expand in the western United States despite future novel conditions
Abstract Distributions of both native and invasive species are expected to shift under future climate. Species distribution models (SDMs) are often used to explore future habitats, but sources of uncertainty including novel climate conditions may reduce the reliability of future projections. We explore the potential spread of the invasive annual grass ventenata ( Ventenata dubia ) in the western United States under both current and future climate scenarios using boosted regression tree models and 30 global climate models (GCMs). We quantify novel climate conditions, prediction variability arising from both the SDMs and GCMs, and the agreement among GCMs. Results demonstrate that currently suitable habitat is concentrated inside the invaded range of the northwest, but substantial habitat exists outside the invaded range in the Southern Rockies and southwestern US mountains. Future suitability projections vary greatly among GCMs, but GCMs commonly projected decreased suitability in the invaded range and increased suitability along higher elevations of interior mountainous areas. Climate novelty did not appear to undermine the prediction reliability in many cases where the climate–species relationship was fully represented by the occurrence data. GCM‐derived variability resulting from variation in future cool season precipitation and temperature seasonality was greatest in the Rocky Mountains. SDM‐derived variability was higher in currently suitable habitat, and few GCMs projections agreed that these areas would contain future suitable habitat. However, while prediction variability was high, many GCM projections agreed that parts of the Rocky, Wasatch, and Uinta Mountains would contain highly suitable habitat in the future. As disturbances in the interior mountains occur in coming decades, reducing some natural barriers to invasion, land managers, and conservationists will need to monitor for ventenata in post‐disturbance environments. Changes to invasion potential may not play out for several decades, but results related to current potential may have applications for early detection and rapid response planning.
Environmental Sciences & Ecology↗
Reconfiguration of power grids during abnormal conditions using reclosers and distributed energy resources
Apparatus and methods are disclosed for restoring operation of a power grid comprising a plurality of reclosers and distributed energy resources (DERs) responsive to abnormal conditions by determining and implementing a reconfiguration for the power grid. The reconfiguration can specify respective new statuses for one or more of the reclosers and/or respective quantities of reactive power to be supplied by one or more of the DERs. The reconfiguration can be determined based on a plurality of constraints using an objective function, the constraints being determined based at least in part on recloser status data and/or DER power generation capability data. Respective cleared quantities of reactive power for the DERs to supply to the reconfigured power grid can be determined via a transactive control scheme, and the reconfiguration can be updated prior to implementation based on the results of the transactive control scheme.
Radhakrishnan, Nikitha↗
Multihierarchy Gaussian Process Models for Probabilistic Aerodynamic Databases using Uncertain Nominal and Off-Nominal Configuration Data
Probabilistic aerodynamic databases are a crucial component of the development lifecycle for aerospace vehicles. A key challenge when building aerodynamic databases is that most data used to construct them represent various simplifications of the real flight vehicle. For example, wind tunnel models often simplify the vehicle geometry and surface roughness characteristics, while CFD computations often make simplifications to the physics being modeled, such as fully laminar or turbulent calculations. Multifidelity data fusion models rely on a user being able to define a hierarchy of fidelity levels anchored to some "truth" data. This approach is unsatisfactory when no data can be considered to accurately reflect real flight conditions. In this work, we provide an alternative approach by presenting a consistent mathematical framework for building probabilistic aerodynamic databases in the form of a conditional probability distribution described by an ensemble of multifidelity Gaussian Processes. Instead of relying on a single hierarchy of data fidelity levels, the presented framework identifies a "nominal" configuration and potential corrections to the nominal which represent specific physical phenomena not represented in the nominal data. The nominal and correction functions themselves are constructed as multifidelity Gaussian Processes and linearly combined to form an ensemble model which fuses the uncertainties associated nominal and correction models. Results obtained using the proposed framework on a simplified Orion Crew Module wind tunnel dataset demonstrate the predictive capability of the multihierarchy framework. We further demonstrate the benefits of such a probabilistic aerodynamic database approach through function sampling and computing the conditional distributions of derived quantities, such as the trim angle of attack and aerodynamic coefficients at trim.
Gaussian Processes↗
Coordination in a hierarchical multi-actuator controller
A hierarchical multi-actuator controller is represented as a multi-resolutional information (knowledge) system utilizing a number of intelligent modules with decision making capabilities. The laws of multi-resolutional information (knowledge) organization and processing are presumed to be satisfied including the rules of dealing with redundant knowledge. A general case is considered in which a process to be controlled by a multiplicity of actuators is a distributed one and the condition of distribution can be formulated analytically. Operation of a lumped multi-actuator process is a particular case which has a broad practical application.
Meystel, Alex↗
Reconstruction of atmospheric pollutant concentrations from remote sensing data - An application of distributed parameter observer theory
The reconstruction of a concentration distribution from spatially averaged and noise-corrupted data is a central problem in processing atmospheric remote sensing data. Distributed parameter observer theory is used to develop reconstructibility conditions for distributed parameter systems having measurements typical of those in remote sensing. The relation of the reconstructibility condition to the stability of the distributed parameter observer is demonstrated. The theory is applied to a variety of remote sensing situations, and it is found that those in which concentrations are measured as a function of altitude satisfy the conditions of distributed state reconstructibility.
Koda, M.↗
Hydride structures in Ti-aluminides subjected to high temperature and hydrogen pressure charging conditions
The distribution and chemistry of hydrides produced in single and dual phase alloys with a composition near TiAl have been investigated by using a combination of TEM and X-ray diffraction techniques. The alloys were exposed at 650 C to 13.8 MPa of gaseous H2 for 100 h. In the single-phase gamma alloy, large hydrides preferentially nucleated on the grain boundaries and matrix dislocations and a population of small hydrides was distributed throughout the matrix. X-ray and electron diffraction patterns from these hydrides indicated that they have an fcc structure with a lattice parameter of 0.45 nm. EDAX analysis of the hydrides showed that they were enriched in Ti. The hydrides were mostly removed by vacuum annealing at 800 C for 24 h. On dissolution of the hydrides, the chemistry of hydride-free regions of the grain boundary returned to the matrix composition, suggesting that Ti segregation accompanied the hydride formation rather than Ti enrichment causing the formation of the hydride.
Legzdina, D.↗
Vector wind and vector wind shear models 0 to 27 km altitude for Cape Kennedy, Florida, and Vandenberg AFB, California
The techniques are presented to derive several statistical wind models. The techniques are from the properties of the multivariate normal probability function. Assuming that the winds can be considered as bivariate normally distributed, then (1) the wind components and conditional wind components are univariate normally distributed, (2) the wind speed is Rayleigh distributed, (3) the conditional distribution of wind speed given a wind direction is Rayleigh distributed, and (4) the frequency of wind direction can be derived. All of these distributions are derived from the 5-sample parameter of wind for the bivariate normal distribution. By further assuming that the winds at two altitudes are quadravariate normally distributed, then the vector wind shear is bivariate normally distributed and the modulus of the vector wind shear is Rayleigh distributed. The conditional probability of wind component shears given a wind component is normally distributed. Examples of these and other properties of the multivariate normal probability distribution function as applied to Cape Kennedy, Florida, and Vandenberg AFB, California, wind data samples are given. A technique to develop a synthetic vector wind profile model of interest to aerospace vehicle applications is presented.
Smith, O. E.↗
Avalanche Photodiode Statistics in Triggered-avalanche Detection Mode
The output of a triggered avalanche mode avalanche photodiode is modeled as Poisson distributed primary avalanche events plus conditionally Poisson distributed trapped carrier induced secondary events. The moment generating function as well as the mean and variance of the diode output statistics are derived. The dispersion of the output statistics is shown to always exceed that of the Poisson distribution. Several examples are considered in detail.
Tan, H. H.↗
ELT antenna gain distributions under simulated crash conditions
A study of the relative merits of ELT antenna positions, when mounted on a small aircraft, is presented. The gain distribution of the best antenna position together with the worst crash scenario is also given.
Estep, H.↗
Approaches in the determination of plant nutrient uptake and distribution in space flight conditions
The effective growth and development of vascular plants rely on the adequate availability of water and nutrients. Inefficiency in either the initial absorption, transportation, or distribution of these elements are factors which impinge on plant structure and metabolic integrity. The potential effect of space flight and microgravity conditions on the efficiency of these processes is unclear. Limitations in the available quantity of space-grown plant material and the sensitivity of routine analytical techniques have made an evaluation of these processes impractical. However, the recent introduction of new plant cultivating methodologies supporting the application of radionuclide elements and subsequent autoradiography techniques provides a highly sensitive investigative approach amenable to space flight studies. Experiments involving the use of gel based 'nutrient packs' and the radionuclides calcium-45 and iron-59 were conducted on the Shuttle mission STS-94. Uptake rates of the radionuclides between ground and flight plant material appeared comparable.
manned↗