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Jia Huo - One of the best experts on this subject based on the ideXlab platform.
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studies on the time Response Distribution of insigh hxmt le
arXiv: Instrumentation and Methods for Astrophysics, 2019Co-Authors: X F Zhao, Y Zhu, D W Han, W W Cui, Juan Wang, Y Wang, Yi Zhang, Yanji Yang, Jia Huo, Z D ZhangAbstract:The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite. The Low Energy X-ray Telescope (LE) is one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 with L-shaped transfer electrodes. Charges in detection area are read out continuously along specific paths, which leads to a time Response Distribution of photons readout time. We designed a long exposure readout mode to measure the time Response Distribution. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. Through analysis of the photons readout time in this mode, we obtained the probability Distribution of photons readout time.
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studies on the time Response Distribution of insight hxmt le
Journal of High Energy Astrophysics, 2019Co-Authors: X F Zhao, Y Zhu, D W Han, W W Cui, Juan Wang, Y Wang, Yi Zhang, Yanji Yang, Jia HuoAbstract:Abstract The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite, with the Low Energy X-ray Telescope (LE) as one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 using L-shaped transfer electrodes. To measure the time Response Distribution resulted from the continuous readout of charges in detection area along specific paths, a long exposure readout mode has been designed. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. And an analysis of the photons readout time in this mode is carried out, to obtain the time Response Distribution.
Y Zhu - One of the best experts on this subject based on the ideXlab platform.
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studies on the time Response Distribution of insigh hxmt le
arXiv: Instrumentation and Methods for Astrophysics, 2019Co-Authors: X F Zhao, Y Zhu, D W Han, W W Cui, Juan Wang, Y Wang, Yi Zhang, Yanji Yang, Jia Huo, Z D ZhangAbstract:The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite. The Low Energy X-ray Telescope (LE) is one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 with L-shaped transfer electrodes. Charges in detection area are read out continuously along specific paths, which leads to a time Response Distribution of photons readout time. We designed a long exposure readout mode to measure the time Response Distribution. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. Through analysis of the photons readout time in this mode, we obtained the probability Distribution of photons readout time.
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studies on the time Response Distribution of insight hxmt le
Journal of High Energy Astrophysics, 2019Co-Authors: X F Zhao, Y Zhu, D W Han, W W Cui, Juan Wang, Y Wang, Yi Zhang, Yanji Yang, Jia HuoAbstract:Abstract The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite, with the Low Energy X-ray Telescope (LE) as one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 using L-shaped transfer electrodes. To measure the time Response Distribution resulted from the continuous readout of charges in detection area along specific paths, a long exposure readout mode has been designed. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. And an analysis of the photons readout time in this mode is carried out, to obtain the time Response Distribution.
Dan G Cacuci - One of the best experts on this subject based on the ideXlab platform.
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TOWARDS OVERCOMING THE CURSE OF DIMENSIONALITY IN PREDICTIVE MODELLING AND UNCERTAINTY QUANTIFICATION
'EDP Sciences', 2021Co-Authors: Dan G CacuciAbstract:This invited presentation summarizes new methodologies developed by the author for performing high-order sensitivity analysis, uncertainty quantification and predictive modeling. The presentation commences by summarizing the newly developed 3rd-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for linear systems, which overcomes the “curse of dimensionality” for sensitivity analysis and uncertainty quantification of a large variety of model Responses of interest in reactor physics systems. The use of the exact expressions of the 2nd-, and 3rd-order sensitivities computed using the 3rd-ASAM is subsequently illustrated by presenting 3rd-order formulas for the first three cumulants of the Response Distribution, for quantifying Response uncertainties (covariance, skewness) stemming from model parameter uncertainties. The use of the 1st-, 2nd-, and 3rd-order sensitivities together with the formulas for the first three cumulants of the Response Distribution are subsequently used in the newly developed 2nd/3rd-BERRU-PM (“Second/Third-Order
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second order adjoint sensitivity analysis methodology 2nd asam for computing exactly and efficiently first and second order sensitivities in large scale linear systems
Journal of Computational Physics, 2015Co-Authors: Dan G CacuciAbstract:This work presents an illustrative application of the second-order adjoint sensitivity analysis methodology (2nd-ASAM) to a paradigm neutron diffusion problem, which is sufficiently simple to admit an exact solution, thereby making transparent the underlying mathematical derivations. The general theory underlying 2nd-ASAM indicates that, for a physical system comprising N α parameters, the computation of all of the first- and second-order Response sensitivities requires (per Response) at most ( 2 N α + 1 ) "large-scale" computations using the first-level and, respectively, second-level adjoint sensitivity systems (1st-LASS and 2nd-LASS). Very importantly, however, the illustrative application presented in this work shows that the actual number of adjoint computations needed for computing all of the first- and second-order Response sensitivities may be significantly less than ( 2 N α + 1 ) per Response. For this illustrative problem, four "large-scale" adjoint computations sufficed for the complete and exact computations of all 4 first- and 10 distinct second-order derivatives. Furthermore, the construction and solution of the 2nd-LASS requires very little additional effort beyond the construction of the adjoint sensitivity system needed for computing the first-order sensitivities. Very significantly, only the sources on the right-sides of the diffusion (differential) operator needed to be modified; the left-side of the differential equations (and hence the "solver" in large-scale practical applications) remained unchanged.All of the first-order relative Response sensitivities to the model parameters have significantly large values, of order unity. Also importantly, most of the second-order relative sensitivities are just as large, and some even up to twice as large as the first-order sensitivities. In the illustrative example presented in this work, the second-order sensitivities contribute little to the Response variances and covariances. However, they have the following major impacts on the computed moments of the Response Distribution: (a) they cause the "expected value of the Response" to differ from the "computed nominal value of the Response"; and (b) they contribute decisively to causing asymmetries in the Response Distribution. Indeed, neglecting the second-order sensitivities would nullify the third-order Response correlations, and hence would nullify the skewness of the Response. Consequently, any events occurring in a Response's long and/or short tails, which are characteristic of rare but decisive events (e.g., major accidents, catastrophes), would likely be missed. The 2nd-ASAM is expected to affect significantly other fields that need efficiently computed second-order Response sensitivities, e.g., optimization, data assimilation/adjustment, model calibration, and predictive modeling. We apply the second-order adjoint sensitivity analysis methodology (2nd-ASAM) to a paradigm diffusion problem.Four 2nd-ASAM adjoint computations exactly determine all fourteen 1st- and 2nd-order sensitivities.Non-zero second-order Response sensitivities decisively skew Response Distributions.
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elements of high order predictive model calibration algorithms with applications to large scale reactor physics systems
2012Co-Authors: Dan G Cacuci, Yousry Y Azmy, William Cyrus ProctorAbstract:The inevitable discrepancies between experimental and computational results provide the basic motivation for performing quantitative model verification, validation, and predictive estimation. Loosely speaking, “code verification” addresses the question “are you solving the mathematical model correctly?”, while model validation addresses the question “does the model represent reality?” Ultimately, one aims at obtaining a probabilistic description of possible future outcomes based on all recognized errors and uncertainties, from all steps in the sequence of modeling and simulation processes that leads to a prediction using a computational model. Achieving this goal requires the combination (“assimilation”) of computational and experimental results in order to adjust (“calibrate”) the model parameters for predicting results (“Responses”) more accurately—the so-called “best-estimate” results, with smaller uncertainties. The mathematical frameworks for combining experimental and computational quantities are customarily called “data adjustment” (for time-independent reactor physics applications) or “data assimilation” (for time-dependent geophysical applications). Notably, the current state-of-the-art procedures for data adjustment and/or assimilation are restricted to the use of second-order uncertainties (i.e., covariance matrices), and do not have provisions for incorporating Response derivatives higher than first-order (in data adjustment procedures) or second-order (in some limited-scope research-versions of data assimilation procedures). Furthermore, neither the data adjustment nor the data assimilation procedures are currently able of computing higher-order moments (e.g., skewness and kurtosis) of the Response Distribution. In the absence of these higher-order moments of the Response Distribution, the predicted Response Distribution must implicitly be assumed as being Gaussian, since it is not possible to quantify the departures, if any, of the predicted Responses from the assumed Gaussian Distribution. An important aspect of the novel contributions presented in this dissertation is the development of highly parallel and scalable algorithms for application of data adjustment and assimilation to large (peta)-scale systems, thereby significantly extending the practical feasibility and applicability of predictive model calibration activities. These new algorithms also include mathematical verification procedures for identifying non-physical covariance matrices, as well as quantifying the consistency of computational and experimental information. Furthermore, the dissertation presents expressions for computing the skewness and kurtosis of Response Distributions, to be used for quantifying non-Gaussian features of computed Response Distributions. A novel method, using adjoint functions, for computing very efficiently second-order mixed derivatives of Responses to parameters, is also presented in this work. The significant impact of the above algorithmic advances is demonstrated by using the neutron transport code Denovo, a highly parallel (one the order of tens of thousands of processors) code that runs on ORNL's leadership-class computer Jaguar, in conjunction with experimental results from the Lady Godiva and Jezebel benchmarks, as well as the “LEU-COMP-THERM-008” (shorthand: LCT) assembly. We recall here that the Lady Godiva benchmark is a bare sphere containing 94 wt% 235U , Jezebel is a critical assembly containing 239Pu , and the LCT assembly models a 3 × 3 array of Pressurized Water Reactor fuel assemblies comprising 4808 fuel rods and 153 water holes. Noteworthy new results in this dissertation are also obtained by using the remarkable efficiency of the “adjoint sensitivity analysis procedure for operator-type Responses”, originally developed by Cacuci in 1981, to compute the sensitivities (derivatives) of the spatially dependent (as opposed to point-values of) neutron fluxes to cross sections. The results obtained in this work represent first-of-a-kind computations of Response skewness and kurtosis, thus enabling a quantitative assessment of non-Gaussian features of predicted Responses (results). In particular, the illustrative results presented for the Godiva, Jezebel, and LCT benchmarks show that the Response skewness and kurtosis are relatively small, thus quantitatively confirming the intuitive feeling (based on the presumed applicability of the central limit theorem) that simple reactor physics problems involving small cross section uncertainties tend to produce reaction rate Responses that are nearly normally distributed. Finally, yet importantly, the algorithmic advances and results presented in this dissertation represent a fundamental first step towards developing a high-order predictive model calibration procedure capable of Bayesian combination of non-Gaussian model parameter features with non-Gaussian experimental Distributions. Such developments are currently underway, and their successful completion is expected to enable more accurate predictions of “best-estimate results” including corresponding predicted non-Gaussian features, for large (peta- and exa-) scale systems.
Dan Gabriel Cacuci - One of the best experts on this subject based on the ideXlab platform.
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comprehensive second order adjoint sensitivity analysis methodology 2nd asam applied to a subcritical experimental reactor physics benchmark iv effects of imprecisely known source parameters
Energies, 2020Co-Authors: Ruixian Fang, Dan Gabriel CacuciAbstract:By applying the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to the polyethylene-reflected plutonium (PERP) benchmark, this work presents results for the first- and second-order sensitivities of this benchmark’s leakage Response with respect to the spontaneous fission source parameters. The numerical results obtained for these sensitivities indicate that the 1st-order relative sensitivity of the leakage Response to the source parameters for the two fissionable isotopes in the benchmark are all positive, signifying that an increase in the source parameters will cause an increase in the total neutron leakage from the PERP sphere. The 1st- and 2nd-order relative sensitivities with respect to the source parameters for 239Pu are very small (10−4 or less). In contradistinction, the 1st-order and several 2nd-order relative sensitivities of the leakage Response with respect to the source parameters of 240Pu are large. Large values (e.g., greater than 1.0) are also displayed by several mixed 2nd-order relative sensitivities of the leakage Response with respect to parameters involving the source and: (i) the total cross sections; (ii) the average neutrons per fission; and (iii) the isotopic number densities. On the other hand, the values of the mixed 2nd-order relative sensitivities with respect to parameters involving the source and: (iv) the scattering cross sections; and (v) and the fission cross sections are smaller than 1.0. It is also shown that the effects of the 1st- and 2nd-order sensitivities of the PERP benchmark’s leakage Response with respect to the benchmark’s source parameters on the moments (expected value, variance and skewness) of the PERP benchmark’s leakage Response Distribution are negligibly smaller than the corresponding effects (on the Response Distribution) stemming from uncertainties in the total, fission and scattering cross sections.
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comprehensive second order adjoint sensitivity analysis methodology 2nd asam applied to a subcritical experimental reactor physics benchmark iii effects of imprecisely known microscopic fission cross sections and average number of neutrons per fissio
Energies, 2019Co-Authors: Dan Gabriel Cacuci, Ruixian Fang, Jeffrey A Favorite, Madalina C Badea, F Di RoccoAbstract:The Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) is applied to compute the first-order and second-order sensitivities of the leakage Response of a polyethylene-reflected plutonium (PERP) experimental system with respect to the following nuclear data: Group-averaged isotopic microscopic fission cross sections, mixed fission/total, fission/scattering cross sections, average number of neutrons per fission (), mixed /total cross sections, /scattering cross sections, and /fission cross sections. The numerical results obtained indicate that the 1st-order relative sensitivities for these nuclear data are smaller than the 1st-order sensitivities of the PERP leakage Response with respect to the total cross sections but are larger than those with respect to the scattering cross sections. The vast majority of the 2nd-order unmixed sensitivities are smaller than the corresponding 1st-order ones, but several 2nd-order mixed relative sensitivities are larger than the 1st-order ones. In particular, several 2nd-order sensitivities for 239Pu are significantly larger than the corresponding 1st-order ones. It is also shown that the effects of the 2nd-order sensitivities of the PERP benchmark’s leakage Response with respect to the benchmark’s parameters underlying the average number of neutrons per fission, , on the moments (expected value, variance, and skewness) of the PERP benchmark’s leakage Response Distribution are negligible by comparison to the corresponding effects (on the Response Distribution) stemming from uncertainties in the total cross sections, but are larger than the corresponding effects (on the Response Distribution) stemming from uncertainties in the fission and scattering cross sections.
X F Zhao - One of the best experts on this subject based on the ideXlab platform.
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studies on the time Response Distribution of insigh hxmt le
arXiv: Instrumentation and Methods for Astrophysics, 2019Co-Authors: X F Zhao, Y Zhu, D W Han, W W Cui, Juan Wang, Y Wang, Yi Zhang, Yanji Yang, Jia Huo, Z D ZhangAbstract:The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite. The Low Energy X-ray Telescope (LE) is one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 with L-shaped transfer electrodes. Charges in detection area are read out continuously along specific paths, which leads to a time Response Distribution of photons readout time. We designed a long exposure readout mode to measure the time Response Distribution. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. Through analysis of the photons readout time in this mode, we obtained the probability Distribution of photons readout time.
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studies on the time Response Distribution of insight hxmt le
Journal of High Energy Astrophysics, 2019Co-Authors: X F Zhao, Y Zhu, D W Han, W W Cui, Juan Wang, Y Wang, Yi Zhang, Yanji Yang, Jia HuoAbstract:Abstract The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite, with the Low Energy X-ray Telescope (LE) as one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 using L-shaped transfer electrodes. To measure the time Response Distribution resulted from the continuous readout of charges in detection area along specific paths, a long exposure readout mode has been designed. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. And an analysis of the photons readout time in this mode is carried out, to obtain the time Response Distribution.
