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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Characterizing the Electromagnetic Response of the NOvA Detectors

The NOvA Test Beam Program was commissioned to complement the full-scale NOvA experiment in its goal of measuring neutrino oscillations. The NOvA Experiment consists of a 300-ton Near Detector and a 14-kton Far Detector, both exposed to the same beam, which can be operated in neutrino or antineutrino mode from Fermilab at an off-axis angle of 14.6~mrad. These detectors can discriminate between $\nu_\mu$-CC and $\nu_e$-CC neutrino (or corresponding antineutrino) events, enabling appearance and disappearance measurements of these flavors across the \SI{810}{\kilo\meter} near-to-far detector baseline. From these measurements, the underlying parameters of the three-flavor PMNS oscillations framework are measured. The NOvA Test Beam uses identical technology to the full-scale detectors, but scaled down to 30~tons. It is exposed to a beam of charged particles closely matched to the daughter products of NOvA (anti)neutrino interactions in both energy and species. An instrumented beamline determines both particle momentum and species upstream of the NOvA detector, allowing for a crisp measurement of the NOvA detector response to these known inputs. This dissertation presents an analysis of the electromagnetic response of the NOvA hardware and establishes a framework for incorporating these results to enhance the physics reach of the experiment. Prior to this work, the electromagnetic energy response of the NOvA detector relied primarily on simulation-driven calibration together with a globally applied energy scale uncertainty. The measurements presented here provide direct test beam constraints on the detector response, enabling particle-dependent and potentially energy-dependent uncertainty models derived from controlled electromagnetic inputs.

Myers, Dalton Grant [U. Texas, Austin (main)] (ORC↗
DOE OSTI2023

Spectrum Unfolding with the MC-15

The Multiplicity Counter 15 tube detector or MC-15 is an optimized detector designed for use in the field. It is composed of 15 3 He tubes embedded in high density polyethylene (HDPE). Recent work has explored expanding the use of the MC-15 beyond multiplicity counting to neutron dosimetry applications. Knowledge of the neutron energy spectrum information is required to use a detector as a neutron dosimeter. The MC-15 tube layout is shown in Figure 1. The unique layout makes it possible to use the detector for neutron spectroscopy via spectrum unfolding. Spectrum unfolding requires (1) energy dependence of the detector response, (2) a detector response matrix that precisely quantifies the response to mono-energetic neutrons, (3) an initial guess spectrum, (4) an unfolding algorithm, and (5) measured data (counts in the case of the MC-15). An energy dependent detector response matrix (DRM) can be constructed by considering either each of the three rows of 3 He tubes as a distinct detector or each individual tube as a distinct detector. The HDPE separating the 3 He in the MC-15 provides the distinct energy dependent response for the rows and individual tubes. In this report we detail the development of detector response matrices for the MC-15 and the application of the Los Alamos Unfolding Code (LUC) to both simulated and measured data. Three MC-15 orientations were studied: (1) standard orientation with the MC-15 front facing the source, (2) standard orientation with Cd sheet, (3) 90° orientation with the side of the MC-15 facing the source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-T-299: Small Fields Profiles Correction Through Detectors Spatial Response Functions and Field Size Dependence Analysis

Purpose: To calculate the spatial response function of various radiation detectors, to evaluate the dependence on the field size and to analyze the small fields profiles corrections by deconvolution techniques. Methods: Crossline profiles were measured on a Novalis Tx 6MV beam with a HDMLC. The configuration setup was SSD=100cm and depth=5cm. Five fields were studied (200×200mm2,100×100mm2, 20×20mm2, 10×10mm2and 5×5mm2) and measured were made with passive detectors (EBT3 radiochromic films and TLD700 thermoluminescent detectors), ionization chambers (PTW30013, PTW31003, CC04 and PTW31016) and diodes (PTW60012 and IBA SFD). The results of passive detectors were adopted as the actual beam profile. To calculate the detectors kernels, modeled by Gaussian functions, an iterative process based on a least squares criterion was used. The deconvolutions of the measured profiles were calculated with the Richardson-Lucy method. Results: The profiles of the passive detectors corresponded with a difference in the penumbra less than 0.1mm. Both diodes resolve the profiles with an overestimation of the penumbra smaller than 0.2mm. For the other detectors, response functions were calculated and resulted in Gaussian functions with a standard deviation approximate to the radius of the detector in study (with a variation less than 3%). The corrected profiles resolve the penumbra with less than 1% error. Major discrepancies were observed for cases in extreme conditions (PTW31003 and 5×5mm2 field size). Conclusion: This work concludes that the response function of a radiation detector is independent on the field size, even for small radiation beams. The profiles correction, using deconvolution techniques and response functions of standard deviation equal to the radius of the detector, gives penumbra values with less than 1% difference to the real profile. The implementation of this technique allows estimating the real profile, freeing from the effects of the detector used for the acquisition.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Application of Polynomial Chaos Expansion in One-Dimensional Inverse Transport Problems

In the problem of inverse radiation transport, measurements of particle leakages from radioactive source/shield systems are used to infer unknown parameters within the systems. This reconstruction can be accomplished by finding the physical parameters of the unknown system that minimize the difference between calculated detector responses and measured detector responses. The inverse transport solver should also propagate uncertainties from the detector responses to the reconstructed parameter values. Recently, the Differential Evolution Adaptive Metropolis (DREAM) method was shown to be a robust method for uncertainty quantification in inverse problems. The DREAM method uses the differential evolution algorithm to choose efficient steps in a Markov chain Monte Carlo (MCMC) simulation. Although the DREAM method has been shown to be more efficient than traditional MCMC approaches, it still requires thousands of transport computations to accurately quantify uncertainty. For the simple ray-tracing model, it was possible to perform these calculations in a reasonable amount of time (under an hour). However, inverse transport problems that require computationally-intensive transport solvers will need prohibitively long run times when using the DREAM method. A way to overcome the computational burden of the DREAM method is to perform surrogate modeling using the polynomial chaos expansion (PCE) approach. It was recently shown that the PCE method provides both accurate and computationally inexpensive uncertainty quantification in forward radiation source/shield problems. PCE was also recently applied to an inverse problem in nonlinear point reactor kinetics within a standard MCMC approach. PCE was first used with the DREAM method where it was applied to inverse problems in groundwater modeling.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

GADRAS-DRF User's Manual (V.18.5)

The Gamma Detector Response and Analysis Software - Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, and estimating source energy distributions from measured spectra. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

Horne, Steven M.↗
DOE OSTI2016

GADRAS-DRF 18.6 User's Manual

The Gamma Detector Response and Analysis Software–Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, and estimating source energy distributions from measured spectra. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

GADRAS-DRF 18.5 User's Manual

The Gamma Detector Response and Analysis Software--Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, and estimating source energy distributions from measured spectra. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

GADRAS-DRF Version 18 User's Manual

The Gamma Detector Response and Analysis Software Detector Response Function (GADRAS-DRF) application computes the response of gamma-ray and neutron detectors to incoming radiation and provides analysis on measured spectra. This manual provides step-by-step procedures to acquaint new users with the use of the application. The capabilities include characterization of detector response parameters, plotting and viewing measured and computed spectra, analyzing spectra to identify isotopes, estimating source energy distributions from measured spectra, and creating inject data. GADRAS-DRF can compute and provide detector responses quickly and accurately, giving users the ability to obtain usable results in a timely manner (a matter of seconds or minutes).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗