URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research

Abstract

Abstract. The understanding of neutron transport by Monte Carlo simulations led to major advancements towards precise interpretation of measurements. URANOS (Ultra Rapid Neutron-Only Simulation) is a free software package which has been developed in the last few years in cooperation with particle physics and environmental sciences, specifically for the purposes of cosmic-ray neutron sensing (CRNS). Its versatile user interface and input/output scheme tailored for CRNS applications offers hydrologists straightforward access to model individual scenarios and to directly perform advanced neutron transport calculations. The geometry can be modeled layer-wise, whereas in each layer a voxel geometry is extruded using a two-dimensional map from pixel images representing predefined materials and allowing for the construction of objects on the basis of pixel graphics without a three-dimensional editor. It furthermore features predefined cosmic-ray neutron spectra and detector configurations and also allows for a replication of important site characteristics of study areas – from a small pond to the catchment scale. The simulation thereby gives precise answers to questions like from which location do neutrons originate? How do they propagate to the sensor? What is the neutron's response to certain environmental changes? In recent years, URANOS has been successfully employed by a number of studies, for example, to calculate the cosmic-ray neutron footprint, signals in complex geometries like mobile applications on roads, urban environments and snow patterns.

Buoy‐Based Detection of Low‐Energy Cosmic‐Ray Neutrons to Monitor the Influence of Atmospheric, Geomagnetic, and Heliospheric Effects

“…Hence, the measured average count rate of 416 cph on the lake is in best agreement with the theoretical value of the "MCNP drf" parameter set from Köhli et al (2021) for θ → ∞. The agreement is certainly within the uncertainty band of the data (see Figure 3), while the remaining discrepancy could arise from a non-negligible effect of neutrons produced by the buoy material and the lead batteries themselves (Köhli et al, 2018(Köhli et al, , 2023Schrön, Rosolem, et al, 2018).…”

“…The surrounding is flat land with mainly natural vegetation. In the preparation of this study, the URANOS model by Köhli et al (2023) was used to simulate the origin of the detected neutrons, following the signal contribution concept presented by Köhli et al (2015) and Schrön et al (2023). The environment was modeled in a 700 × 700 m 2 domain (Figure 1b) with a virtual detector above water, a given land structure with 10% soil moisture, and air with 10 g/m 3 ; humidity.…”

Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field

“…where w j is the weight for sampling interval j (Equation ( 12)) and θ j is the gravimetric water content value for sampling interval j. Note, for a more complete treatment of support volume, Monte Carlo particle transport codes like MCNP or URANOS may be used [50,54,63,73].…”

“…The CRNS community has also taken advantage of simulation methods, such as Monte Carlo N-Particle Transport (MCNP) code and the Ultra Rapid Adaptable Neutron-Only Simulation (URANOS), to answer a variety of questions about footprint characteristics and sources of signal attenuation [73]. Topics explored in CRNS simulations that warrant study in gamma-ray simulations as well include footprint size for different energy ranges of detection [49,50,80], measurement capabilities in heterogenous landscapes [52,81], and performance in the presence of factors such as air humidity and fractional snow cover [82,83].…”

Toward Large‐Scale Soil Moisture Monitoring Using Rail‐Based Cosmic Ray Neutron Sensing

“…Neutron simulation software, allows to predict the amount of neutron counts for given site conditions and sensor charateritics and has helped to interpret the understanding of soil-neutron-sensor interactions in the last years (e.g., Andreasen et al, 2016;Köhli et al, 2015Köhli et al, , 2018Zreda et al, 2008). Novel three-dimensional simulations, for example, performed by URANOS (Köhli et al, 2023) further support the disentangling of the signal integral and helped to define a practical footprint definition and that considers the relative contribution of remote or nearby areas (e.g., Schrön et al, 2023). While these advances have increased the understanding of the signal origin and allow for more precise interpretations, the mapped area of stationary CRNS remains restricted to its static footprint.…”