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Feldman, Alexander

Publications and source records attributed to Feldman, Alexander.

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine learning based systems and methods for real time, model based diagnosis

The disclosure following relates generally to complex simulations, and fault diagnosis. In some embodiments, a component that is causing a delayed simulation time of a system is determined. A component of reduced complexity is designed, and the component of reduced complexity is used to replace the original component in the system. Fault diagnosis may then be conducted using the updated system with the reduced complexity component, thus decreasing the time taken to diagnose the fault.

Matei, Ion↗
DOE OSTI2022

SCO#1197 Addendum #4 OSR Characterization Database (Test Report)

A test plan was developed and approved in June of 2022. Testing was successfully performed to verify the functions of Version 2.0 of the OSR Characterization database. Checks verified that data remains consistent to tests previously performed using Microsoft Access® 2003, 2010 and 2016.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Applying Simulated Annealing to Problems in Model-Based Diagnosis

Generating all diagnoses is computationally intractable. Therefore, many of the state-of-the-art approaches are incomplete. Quantum computers may however offer a solution. The first commercially available quantum computer is being used to minimize polynomials that are difficult for classical simulated annealing but easy for quantum annealing. All problems in Model-based Diagnosis (MBD) can be transformed into a polynomial minimization problem, allowing one to apply a quantum algorithm called quantum annealing to solve MBD problems. To better understand the need for this quantum approach, we designed two simulated annealingdiagnostic algorithms tailored to run on a polynomial representation of MBD. These algorithms differ on their policy for random neighborhood variable selection. In addition, enhanced metrics were devised to provide more diagnostic coverage. Finally, these two simulated annealing algorithms were analyzed and empirically evaluated and compared against state-of-the-art probabilistic methods for MBD such as SAFARI using ISCAS-85.

Simulated annealing↗
DOE OSTI2014

Radiological Characterization Technical Report on Californium-252 Sealed Source Transuranic Debris Waste for the Off-Site Source Recovery Project at Los Alamos National Laboratory

This document describes the development and approach for the radiological characterization of Cf-252 sealed sources for shipment to the Waste Isolation Pilot Plant. The report combines information on the nuclear material content of each individual source (mass or activity and date of manufacture) with information and data on the radionuclide distributions within the originating nuclear material. This approach allows for complete and accurate characterization of the waste container without the need to take additional measurements. The radionuclide uncertainties, developed from acceptable knowledge (AK) information regarding the source material, are applied to the summed activities in the drum. The AK information used in the characterization of Cf-252 sealed sources has been qualified by the peer review process, which has been reviewed and accepted by the Environmental Protection Agency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Cf-252 Characterization Documents

Six documents were written by Vance and Associates under contract to the Off-Site Source Recovery Project of Los Alamos National Laboratory. These Six documents provided the basis for characterization of Californium-252 sealed sources and for the packaging and manifesting of this material for disposal at the Waste Isolation Pilot Project. The Six documents are: 1. VA-OSR-10, Development of radionuclide distributions for Cf-252 sealed sources. 2. VA-OSR-11, Uncertainty analysis for Cf-252 sealed sources. 3. VA-OSR-12, To determine the radionuclides in the waste drums containing Cf-252 sealed source waste that are required to be reported under the requirements of the WIPP WAC and the TRAMPAC. 4. VA-OSR-13, Development of the spreadsheet for the radiological calculations for the characterization of Cf-252 sources. 5. VA-OSR-14, Relative importance of neutron-induced fission in Cf-252 sources. 6. VA-OSR-15, Determine upper bound of decay product inventories from a drum of Cf-252 sources. These six documents provide the technical basis for the characterization of Cf-252 sources and will be part of the AK documentation required for submittal to the Central Characterization Project (CCP) of WIPP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2009

First International Diagnosis Competition - DXC'09

A framework to compare and evaluate diagnosis algorithms (DAs) has been created jointly by NASA Ames Research Center and PARC. In this paper, we present the first concrete implementation of this framework as a competition called DXC 09. The goal of this competition was to evaluate and compare DAs in a common platform and to determine a winner based on diagnosis results. 12 DAs (model-based and otherwise) competed in this first year of the competition in 3 tracks that included industrial and synthetic systems. Specifically, the participants provided algorithms that communicated with the run-time architecture to receive scenario data and return diagnostic results. These algorithms were run on extended scenario data sets (different from sample set) to compute a set of pre-defined metrics. A ranking scheme based on weighted metrics was used to declare winners. This paper presents the systems used in DXC 09, description of faults and data sets, a listing of participating DAs, the metrics and results computed from running the DAs, and a superficial analysis of the results.

Kurtoglu, tolga↗
NASA NTRS2009

Towards a Framework for Evaluating and Comparing Diagnosis Algorithms

Diagnostic inference involves the detection of anomalous system behavior and the identification of its cause, possibly down to a failed unit or to a parameter of a failed unit. Traditional approaches to solving this problem include expert/rule-based, model-based, and data-driven methods. Each approach (and various techniques within each approach) use different representations of the knowledge required to perform the diagnosis. The sensor data is expected to be combined with these internal representations to produce the diagnosis result. In spite of the availability of various diagnosis technologies, there have been only minimal efforts to develop a standardized software framework to run, evaluate, and compare different diagnosis technologies on the same system. This paper presents a framework that defines a standardized representation of the system knowledge, the sensor data, and the form of the diagnosis results and provides a run-time architecture that can execute diagnosis algorithms, send sensor data to the algorithms at appropriate time steps from a variety of sources (including the actual physical system), and collect resulting diagnoses. We also define a set of metrics that can be used to evaluate and compare the performance of the algorithms, and provide software to calculate the metrics.

Kurtoglu, Tolga↗