Generation of Spatial Weighting Functions for Ex-Core Detectors by Adjoint Transport Calculation

Neutrons from an atmospheric nuclear explosion can be detected by sensors in orbit. Current tools for characterizing the neutron energy spectrum assume a known source and use forward transport to recreate the detector response. In realistic scenarios the true source is unknown, making this an inefficient, iterative approach. In contrast, the adjoint approach directly solves for the source spectrum, enabling source reconstruction. The time–energy fluence at the satellite and adjoint transport equation allow a Monte Carlo method to characterize the neutron source’s energy spectrum directly in a new model: the Space to High-Altitude Region Adjoint (SAHARA) model. A new adjoint source event estimator was developed in SAHARA to find feasible solutions to the neutron transport problem given the constraints of the adjoint environment. This work explores SAHARA’s development and performance for mono-energetic and continuous neutron energy sources. In general, the identified spectra were shifted towards energies approximately 5% lower than the true source spectra, but SAHARA was able to capture the correct spectral shapes. Continuous energy sources, including real-world sources Fat Man and Little Boy, resulted in identifiable spectra that could have been produced by the same distribution as the true sources as demonstrated by two-dimensional (2D) Kolmogorov–Smirnov tests.

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The Effects of Weighting Functions on the Performances of Robust Control Systems

Proceedings ◽

10.3390/proceedings2020063046 ◽

2020 ◽

Vol 63 (1) ◽

pp. 46

Author(s):

Mircea Dulau ◽

Stelian-Emilian Oltean

Keyword(s):

Robust Control ◽

Control Systems ◽

Tracking Error ◽

Weighting Functions ◽

Loop Control ◽

Frequency Sensitivity ◽

Sensitivity Functions ◽

Loop Control System ◽

Robust Control Design ◽

Robust Control Systems

An important stage in robust control design is to define the desired performances of the closed loop control system using the models of the frequency sensitivity functions S. If the frequency sensitivity functions remain within the limits imposed by these models, the control performances are met. In terms of the sensitivity functions, the specifications include: shape of S over selected frequency ranges, peak magnitude of S, bandwidth frequency, and tracking error at selected frequencies. In this context, this paper presents a study of the effects of the specifications of the weighting functions on the performances of robust control systems.

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Calculation of the weighting functions for the reconstruction of absorbing inhomogeneities in tissue by time-resolved optical projections

Quantum Electronics ◽

10.1070/qe2014v044n08abeh015495 ◽

2014 ◽

Vol 44 (8) ◽

pp. 719-725 ◽

Cited By ~ 4

Author(s):

A B Konovalov ◽

V V Vlasov

Keyword(s):

Weighting Functions ◽

Time Resolved

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Computational Fluid Dynamics Modeling of Steam Condensation on Nuclear Containment Wall Surfaces Based on Semiempirical Generalized Correlations

Science and Technology of Nuclear Installations ◽

10.1155/2012/106759 ◽

2012 ◽

Vol 2012 ◽

pp. 1-7 ◽

Cited By ~ 6

Author(s):

Pavan K. Sharma ◽

B. Gera ◽

R. K. Singh ◽

K. K. Vaze

Keyword(s):

Nuclear Power ◽

Nuclear Reactor ◽

Pressure Rise ◽

Dynamics Modeling ◽

Steam Condensation ◽

Noncondensable Gases ◽

Nuclear Containment ◽

Design Basis ◽

Lumped Parameter ◽

Transport Calculation

In water-cooled nuclear power reactors, significant quantities of steam and hydrogen could be produced within the primary containment following the postulated design basis accidents (DBA) or beyond design basis accidents (BDBA). For accurate calculation of the temperature/pressure rise and hydrogen transport calculation in nuclear reactor containment due to such scenarios, wall condensation heat transfer coefficient (HTC) is used. In the present work, the adaptation of a commercial CFD code with the implementation of models for steam condensation on wall surfaces in presence of noncondensable gases is explained. Steam condensation has been modeled using the empirical average HTC, which was originally developed to be used for “lumped-parameter” (volume-averaged) modeling of steam condensation in the presence of noncondensable gases. The present paper suggests a generalized HTC based on curve fitting of most of the reported semiempirical condensation models, which are valid for specific wall conditions. The present methodology has been validated against limited reported experimental data from the COPAIN experimental facility. This is the first step towards the CFD-based generalized analysis procedure for condensation modeling applicable for containment wall surfaces that is being evolved further for specific wall surfaces within the multicompartment containment atmosphere.

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