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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

Environmental transition zones are associated with geochemical gradients that overcome energy limitations to microbial metabolism, resulting in biogeochemical hot spots and moments. Riverine systems where groundwater mixes with surface water (the hyporheic zone) are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. To investigate the coupling among groundwater-surface water mixing, microbial communities, and biogeochemistry we applied ecological theory, aqueous biogeochemistry, DNA sequencing, and ultra-high resolution organic carbon profiling to field samples collected across times and locations representing a broad range of mixing conditions. Mixing of groundwater and surface water resulted in a shift from transport-driven stochastic dynamics to a deterministic microbial structure associated with elevated biogeochemical rates. While the dynamics of the hyporheic make predictive modeling a challenge, we provide new knowledge that can improve the tractability of such models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Utilizing grid–supportive load response to shape resilient frequency control of the power grid

The increasing penetration of renewable energy sources and the retirement of conventional generation units have decreased system inertia, making power systems more vulnerable to resilience and stability issues. To address this problem, this paper proposes a novel approach using grid-supportive loads (GSLs) to provide a fast and concise primary frequency response and a deep deterministic policy gradient agent-based secondary controller to restore the system frequency to the nominal value. The proposed method is evaluated on the single-area and multi-area test systems. The simulation results demonstrate that using GSLs enhances the power system's stability and resilience. Compared to conventional controllers, the frequency nadir is improved with GSLs. Additionally, the proposed method effectively enhances resilience even with high penetration. These findings indicate that the proposed approach can improve the resilience and stability of power systems and provide a promising solution for future power systems. The results of this study underscore the importance of utilizing innovative approaches to enhance the stability and resilience of power systems in the context of high penetration of renewable energy sources and the retirement of conventional generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Accurate modeling of switched reluctance machine based on hybrid trained WNN

According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Chaos in an imperfectly premixed model combustor

This article reports nonlinear bifurcations observed in a laboratory scale, turbulent combustor operating under imperfectly premixed mode with global equivalence ratio as the control parameter. The results indicate that the dynamics of thermoacoustic instability correspond to quasi-periodic bifurcation to low-dimensional, deterministic chaos, a route that is common to a variety of dissipative nonlinear systems. The results support the recent identification of bifurcation scenarios in a laminar premixed flame combustor (Kabiraj et al., Chaos: Interdiscip. J. Nonlinear Sci. 22, 023129 (2012)) and extend the observation to a practically relevant combustor configuration.

42 ENGINEERING↗
DOE OSTI2015

A fixed mass method for the Kramers-Moyal expansion—Application to time series with outliers

Extraction of stochastic and deterministic components from empirical data—necessary for the reconstruction of the dynamics of the system—is discussed. We determine both components using the Kramers-Moyal expansion. In our earlier papers, we obtained large fluctuations in the magnitude of both terms for rare or extreme valued events in the data. Calculations for such events are burdened by an unsatisfactory quality of the statistics. In general, the method is sensitive to the binning procedure applied for the construction of histograms. Instead of the commonly used constant width of bins, we use here a constant number of counts for each bin. This approach—the fixed mass method—allows to include in the calculation events, which do not yield satisfactory statistics in the fixed bin width method. The method developed is general. To demonstrate its properties, here, we present the modified Kramers-Moyal expansion method and discuss its properties by the application of the fixed mass method to four representative heart rate variability recordings with different numbers of ectopic beats. These beats may be rare events as well as outlying, i.e., very small or very large heart cycle lengths. The properties of ectopic beats are important not only for medical diagnostic purposes but the occurrence of ectopic beats is a general example of the kind of variability that occurs in a signal with outliers. To show that the method is general, we also present results for two examples of data from very different areas of science: daily temperatures at a large European city and recordings of traffics on a highway. Using the fixed mass method, to assess the dynamics leading to the outlying events we studied the occurrence of higher order terms of the Kramers-Moyal expansion in the recordings. We found that the higher order terms of the Kramers-Moyal expansion are negligible for heart rate variability. This finding opens the possibility of the application of the Langevin equation to the whole range of empirical signals containing rare or outlying events. Note, however, that the higher order terms are non-negligible for the other data studied here and for it the Langevin equation is not applicable as a model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Spin-system dynamics and fault detection in threshold networks

We consider an agent on a fixed but arbitrary node of a known threshold network, with the task of detecting an unknown missing link. We obtain analytic formulas for the probability of success when the agent's tool is the free evolution of a single excitation on an XX spin system paired with the network. We completely characterize the parameters, which allows us to obtain an advantageous solution. From the results emerges an optimal (deterministic) algorithm for quantum search, from which a quadratic speedup with respect to the optimal classical analog and in line with well-known results in quantum computation is gained. When attempting to detect a faulty node, the chosen setting appears to be very fragile and the probability of success too small to be of any direct use.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Test-state approach to the quantum search problem

The search for 'a quantum needle in a quantum haystack' is a metaphor for the problem of finding out which one of a permissible set of unitary mappings - the oracles - is implemented by a given black box. Grover's algorithm solves this problem with quadratic speedup as compared with the analogous search for 'a classical needle in a classical haystack'. Since the outcome of Grover's algorithm is probabilistic - it gives the correct answer with high probability, not with certainty - the answer requires verification. For this purpose we introduce specific test states, one for each oracle. These test states can also be used to realize 'a classical search for the quantum needle' which is deterministic - it always gives a definite answer after a finite number of steps - and 3.41 times as fast as the purely classical search. Since the test-state search and Grover's algorithm look for the same quantum needle, the average number of oracle queries of the test-state search is the classical benchmark for Grover's algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Neutronics qualification of the Jules Horowitz reactor fuel by interpretation of the VALMONT experimental program - Transposition of the uncertainties on the reactivity of JHR with JEF2.2 and JEFF3.1.1

The new European material testing Jules Horowitz Reactor (JHR), currently under construction in Cadarache center (CEA France), will use LEU (20% enrichment in {sup 235}U) fuels (U{sub 3}Si{sub 2} for the start up and UMoAl in the future) which are quite different from the industrial oxide fuel, for which an extensive neutronics qualification database has been established. The HORUS3D/N neutronics calculation scheme, used for the design and safety studies of the JHR, is being developed within the framework of a rigorous verification-validation-qualification methodology. In this framework, the experimental VALMONT (Validation of Aluminium Molybdenum uranium fuel for Neutronics) program has been performed in the MINERVE facility of CEA Cadarache (France), in order to qualify the capability of HORUS3D/N to accurately calculate the reactivity of the JHR reactor. The MINERVE facility using the oscillation technique provides accurate measurements of reactivity effect of samples. The VALMONT program includes oscillations of samples of UAl{sub x}/Al and UMo/Al with enrichments ranging from 0.2% to 20% and Uranium densities from 2.2 to 8 g/cm{sup 3}. The geometry of the samples and the pitch of the experimental lattice ensure maximum representativeness with the neutron spectrum expected for JHR. By comparing the effect of the sample with the one of a known fuel specimen, the reactivity effect can be measured in absolute terms and be compared to computational results. Special attention was paid to the rigorous determination and reduction of the experimental uncertainties. The calculational analysis of the VALMONT results was performed with the French deterministic code APOLLO2. A comparison of the impact of the different calculation methods, data libraries and energy meshes that were tested is presented. The interpretation of the VALMONT experimental program allowed the qualification of JHR fuel UMoAl8 (with an enrichment of 19.75% {sup 235}U) by the Minerve-dedicated interpretation tool: PIMS. The effect of energy meshes and evaluations put forward the JEFF3.1.1/SHEM scheme that leads to a better calculation of the reactivity effect of VALMONT samples. Then, in order to quantify the impact of the uncertainties linked to the basic nuclear data, their propagation from the cross section measurement to the final computational result was analysed in a rigorous way by using a nuclear data re-estimation method based on Gauss-Newton iterations. This study concludes that the prior uncertainties due to nuclear data (uranium, aluminium, beryllium and water) on the reactivity of the Begin Of Cycle (BOC) for the JHR core reach 1217 pcm at 2{sigma}. Now, the uppermost uncertainty on the JHR reactivity is due to aluminium. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Approximate Dynamic Programming With Enhanced Off-Policy Learning for Coordinating Distributed Energy Resources

Herein this paper proposes an innovative approximate dynamic programming (ADP) method for distributed energy resource coordination with the loss of life of battery energy storage system (BESS) explicitly modeled. The dispatch policy is designed to account for both calendrical and cyclical aging effects on BESS, explicitly modeling the impacts of ambient temperature on BESS lifespan. The proposed ADP employs an adaptive critic method and enhanced off-policy deterministic policy gradient (DPG) strategy, addressing the limitations of the on-policy gradient-based ADP approaches, including inadequate exploration, low data usage, and computational complexity. In particular, a customized policy is proposed to guide the algorithm to explore some promising decisions and thereby improve exploration capability and learning efficiency compared to conventional DPG-based learning approaches, which may struggle to find a global optimum due to random noisy action-based exploration or require expert demonstration with extra effort. The proposed method is illustrated using the IEEE 123-node system and compared with the existing ADP methods to prove solution accuracy and demonstrate the effects of incorporating degradation models into control design. Case studies showed that the proposed ADP effectively coordinates DERs with a 10 times smaller optimization gap compared to existing methods, and the incorporation of the BESS life loss model ensures the expected lifespan and results in significant cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

LARGE PARTICLE SEPARATION FROM NON-NEWTONIAN SLURRIES USING BUMP ARRAYS

Here we evaluate the performance of bump arrays to separate large particles from non-Newtonian slurries with Bingham and Cross rheology. Bump arrays in deterministic lateral displacement devices separate large particles from small particles using arrays of staggered posts. Large particles, defined as those with radii larger than the distance between the edge of a post and the stagnation streamline from the next downstream post, must bump toward one side of the device, whereas particles smaller than this distance slalom from entrance to exit. Although these devices have been used to separate a wide variety of large particles from blood cells to sand, partition of large particles from non-Newtonian fluids remains unexplored. Yet, an important set of modestly concentrated slurries, including Hanford nuclear waste, displays non-Newtonian rheology. Here we evaluate the influence of non-Newtonian rheology on the large-small particle size cutoff in bump arrays using a model that explores the influence of yield stresses, ratios of zero and infinite shear viscosities, and Cross’s exponent under strictly laminar well-developed conditions. Surprisingly, we find that viscosity ratios and Cross’s exponent make no significant difference on the particle cutoffs between large particles that bump and small particles that slalom around the posts from entrance to exit. In contrast, we find that yield stresses do significantly affect the size cutoff. As the yield stress increases, the velocity profiles become more plug like lowering the size cutoff. For nuclear waste separations where removing large particles is a priority, increasing yield stresses is conservative.

slurry, solids removal, deterministic later displa↗
DOE OSTI2013

Full Core Reactor Analysis: Running Denovo on Jaguar

Fully-consistent, full-core, 3D, deterministic neutron transport simulations using the orthogonal mesh code Denovo were run on the massively parallel computing architecture Jaguar XT5. Using energy and spatial parallelization schemes, Denovo was able to efficiently scale to more than 160k processors. Cell-homogenized cross sections were used with step-characteristics, linear-discontinuous finite element, and trilinear-discontinuous finite element spatial methods. It was determined that using the finite element methods gave considerably more accurate eigenvalue solutions for large-aspect ratio meshes than using step-characteristics.

Denovo↗
DOE OSTI2016

Application of Monte Carlo Methods to Perform Uncertainty and Sensitivity Analysis on Inverse Water-Rock Reactions with NETPATH

Methods were developed to quantify uncertainty and sensitivity for NETPATH inverse water-rock reaction models and to calculate dissolved inorganic carbon, carbon-14 groundwater travel times. The NETPATH models calculate upgradient groundwater mixing fractions that produce the downgradient target water chemistry along with amounts of mineral phases that are either precipitated or dissolved. Carbon-14 groundwater travel times are calculated based on the upgradient source-water fractions, carbonate mineral phase changes, and isotopic fractionation. Custom scripts and statistical code were developed for this study to facilitate modifying input parameters, running the NETPATH simulations, extracting relevant output, postprocessing the results, and producing graphs and summaries. The scripts read userspecified values for each constituent’s coefficient of variation, distribution, sensitivity parameter, maximum dissolution or precipitation amounts, and number of Monte Carlo simulations. Monte Carlo methods for analysis of parametric uncertainty assign a distribution to each uncertain variable, sample from those distributions, and evaluate the ensemble output. The uncertainty in input affected the variability of outputs, namely source-water mixing, phase dissolution and precipitation amounts, and carbon-14 travel time. Although NETPATH may provide models that satisfy the constraints, it is up to the geochemist to determine whether the results are geochemically reasonable. Two example water-rock reaction models from previous geochemical reports were considered in this study. Sensitivity analysis was also conducted to evaluate the change in output caused by a small change in input, one constituent at a time. Results were standardized to allow for sensitivity comparisons across all inputs, which results in a representative value for each scenario. The approach yielded insight into the uncertainty in water-rock reactions and travel times. For example, there was little variation in source-water fraction between the deterministic and Monte Carlo approaches, and therefore, little variation in travel times between approaches. Sensitivity analysis proved very useful for identifying the most important input constraints (dissolved-ion concentrations), which can reveal the variables that have the most influence on source-water fractions and carbon-14 travel times. Once these variables are determined, more focused effort can be applied to determining the proper distribution for each constraint. Second, Monte Carlo results for water-rock reaction modeling showed discrete and nonunique results. The NETPATH models provide the solutions that satisfy the constraints of upgradient and downgradient water chemistry. There can exist multiple, discrete solutions for any scenario and these discrete solutions cause grouping of results. As a result, the variability in output may not easily be represented by a single distribution or a mean and variance and care should be taken in the interpretation and reporting of results.

phase dissolution and precipitation amounts↗
DOE OSTI2024

Hazards and Probabilistic Risk Assessments of Advanced Nuclear Reactors Coupled with Industrial Facilities

This report provides a roadmap and tool kit for site specific risk assessments across a broad range of industrial customers co-located with advanced nuclear power plants (ANPP) that are not currently built and operating in the U.S. This report builds upon the body of work sponsored by the Department of Energy (DOE) Integrated Energy Systems Pathway that has produced industrial requirements studies and techno-economic assessments on the topics of feasibility of ANPP supported industrial processes. This report also leverages the DOE Light Water Reactor Sustainability (LWRS) program that has presented hazards assessment and generic probabilistic risk assessments (PRAs) for the addition of a heat extraction system (HES) to light-water reactors (LWRs) co-located with hydrogen production facilities. Many of the hazard assessments and risk assessments performed for the LWRS report are agnostic to whether the nuclear reactor is an ANPP or were adapted to the ANPP focus. The report performs hazards assessments to include industrial facilities: an oil refinery, a methanol plant, a synthetic fuel (synfuel) plant, the production of synthetic gas (syngas) as part of the methanol and synfuel plants, wood pulp and paper mills, and hydrogen production. Hydrogen production facilities are assessed in depth through prior reports in the LWRS program and the results are leveraged in this report. All these facilities are specified through industrial process and requirements research performed by national laboratories, universities, and interaction with industry. Many of the processes used in this report are pre-conceptual designs to use for decarbonization of the current technology facilities. A process of failure modes and effects analysis (what can go wrong) and accidentology (what has historically gone wrong) was used to determine the hazards presented to the nuclear power plant by the addition of the HES and the industrial customer. Chemical properties of feedstocks and products are summarized as part of the hazards assessment. Example analysis procedures are provided for each of the hazard types identified. These deterministic analyses can be used to assess adherence to licensing criteria. They can also be used to meet other safety goals like protection of the public, workers, or industrial facility equipment. A modular high temperature gas-cooled reactor (MHTGR) PRA only existing on paper was modeled and verified in modern PRA software. This will provide a tool for representative ANPP probabilistic analyses for future research.

10 SYNTHETIC FUELS↗
DOE OSTI2018

Noise Is Not Error: Detecting Parametric Heterogeneity Between Epidemiologic Time Series

Mathematical models play a central role in epidemiology. For example, models unify heterogeneous data into a single framework, suggest experimental designs, and generate hypotheses. Traditional methods based on deterministic assumptions, such as ordinary differential equations (ODE), have been successful in those scenarios. However, noise caused by random variations rather than true differences is an intrinsic feature of the cellular/molecular/social world. Time series data from patients (in the case of clinical science) or number of infections (in the case of epidemics) can vary due to both intrinsic differences or incidental fluctuations. The use of traditional fitting methods for ODEs applied to noisy problems implies that deviation from some trend can only be due to error or parametric heterogeneity, that is noise can be wrongly classified as parametric heterogeneity. This leads to unstable predictions and potentially misguided policies or research programs. In this paper, we quantify the ability of ODEs under different hypotheses (fixed or random effects) to capture individual differences in the underlying data. We explore a simple (exactly solvable) example displaying an initial exponential growth by comparing state-of-the-art stochastic fitting and traditional least squares approximations. We also provide a potential approach for determining the limitations and risks of traditional fitting methodologies. Finally, we discuss the implications of our results for the interpretation of data from the 2014-2015 Ebola epidemic in Africa.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2023

Mitigating Space Radiation Using Magnesium(-Lithium) and Boron Carbide Composites

The health effects of galactic cosmic radiation are a serious impediment to crewed exploration of the solar system. OLTARIS, an interface for the 3DHZETRN deterministic radiation transport code, was used to assess the response of aerospace materials to this constant radiation exposure. Traditional aerospace structural materials like aluminum can, after a certain mass, increase the health effects of such radiation. However, materials with lower atomic mass may mitigate this build-up in secondary radiation with increasing areal density. As such, lower atomic mass structural alloys of magnesium and magnesium–lithium are promising candidates. These alloys may reduce the mass of structures when substituted for aluminum alloys. Reinforcement with boron carbide could further reduce atomic mass while also improving the mechanical properties of such lightweight alloys. This study found that the lower atomic mass of these materials increased nuclear fragmentation upon cosmic radiation interactions, leading to a softening of the secondary (neutron) radiation spectra. This softened spectra reduced the effective dose equivalent, a measure of health effects, for magnesium(-lithium) alloys and their boron carbide-reinforced composites when compared to aluminum.

Galactic cosmic radiation↗
DOE OSTI2018

Challenges to Evaluating Ecological Risks in Performance Assessments - 18424

Performance assessments (PAs), whether probabilistic or deterministic, have largely focused on evaluating human health effects of radionuclides. In the past, it was asserted that protecting human health would automatically protect the environment. This blanket assertion has been questioned, so tools and methodologies to directly estimate non-human biota dose have been developed and made available since the early 2000's. For example, the Biota Dose Assessment Committee (BDAC) guidance led to the development of the RESRAD-BIOTA (RESRAD stands for Residual Radioactive materials) software to implement this guidance. The BDAC was a US Department of Energy (DOE) led working group with members from academia and consultancies in addition to DOE technical staff. Parallel efforts have been in place in Europe with the development of the ERICA tool (Environmental Risk from Ionising Contaminants: Assessment and Management). More recently, interpretation of the requirements of US Department of Energy (DOE) Order O458.1 have led some waste management facilities to include ecological risks in addition to human health effects in their PAs. We have recently developed methodologies to assess ecological risks within probabilistic PAs (PPAs) for two Federal facilities. One of the challenges in applying the non-human biota assessment models to PPAs is that ecological risk assessments following US Environmental Protection Agency (EPA) or DOE guidance start with protective screening assessments before moving into more site-specific ecological risk assessments. Conservative assumptions bias the screening assessments and greatly overestimate the risks posed by contaminants. However, although the screens are biased they can be useful in ruling out model spatial domain areas or types of biota from requiring further assessment. In some cases, the results of the screen could entirely rule out ecological risks from further assessment. For a more refined and unbiased estimate of dose to non-human biota, one would typically conduct site-specific studies to better define exposure through the food web or adverse effects based on eco-toxicity studies of environmental, and generally weathered, contaminant mixtures. However, for PPAs that consider future site conditions after the loss of institutional control, such site-specific studies are not possible. Rather, site-specific future ecological risk models use probabilistic inputs that result in a distribution of population doses or exposures and calculate the distribution of possible adverse effects to ecological populations. This approach considers both radionuclide and chemical inventory. For both Federal facilities, the model spatial domains include riparian and aquatic environments located downstream of the waste management site. These riparian and aquatic environments represent linear exposure elements for some wildlife populations and require special consideration of exposures to individuals and to populations along such spatial domains. At a minimum, wildlife foraging should be focused along the axis of such water bodies. Another challenge is how to incorporate ecologically relevant spatial scales into models that have contaminant transport as the primary focus. Riparian and aquatic environments also have threatened and endangered (T and E) species, which necessitate greater levels of protection given their rarity. A final challenge for conducting ecological risk assessments is how to evaluate T and E species in the future. This might be addressed by evaluating potential for impacts on individuals of feeding guilds with species that are currently threatened or endangered. We also have to consider how ecological populations might change as a result of climate change. It is a more difficult problem to predict what species might become rare in the future, and how to best assess future populations of threatened or endangered species. (authors)

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

Validation of a Monte Carlo model for the MLC-Elekta Precise with MCNP6 - Paper 76

Cancer treatment using radiotherapy techniques needs an accurate prediction of the dose delivered to the patient at each position. Treatment planning systems (TPS) allow the optimization of the dose delivered to the tumor volume while minimizing the dose absorbed by the surrounding healthy tissue. Commercial treatment planning systems use empirical deterministic algorithms that do not correctly estimate the dose in the surroundings of heterogeneities. This lack of accuracy is taken into account as bigger security margins in the treatment, reducing the potential effect of the treatment. However, Monte Carlo (MC) simulation techniques have proved to predict the dose distribution more accurately and also representing experimental data better. Nevertheless, the clinical application of these techniques has been limited by the long calculation times they require. As high performance computers decrease in cost MC simulations become more feasible to be used in TPS. The present work improves a simplified model of the MLC-Elekta Precise linear accelerator (linac or unit from now on) previously developed and correctly validated by the group. A multileaf collimator (MLC) has been modelled according to the manufacturer specifications and added to the previous model to allow higher conformity in the studies. The full geometry has been entered to the MCNP6 Monte Carlo code to simulate the transport of particles through the linac. The geometry also includes a cubic water phantom for dosimetry studies and validation with experimental data. The experimental data employed for the dose distribution comparison has been measured at the linac from the linac Hospital Universitari Clinic de Valencia (Spain). Additionally, particles are stored in a phase space surface before their entrance in the water to be analyzed and for performance optimization. Given the results presented, we conclude that this first approach to validate a model of the Elekta Precise linac from the Hospital Cl nic Universitari de Valancia represents well the depth-dose distribution, but fails at representing the dose profiles. It has been shown that they predict too much penumbra, probably caused by the filtration between the leaves. In order to solve this problems, further work is needed to improve the simulated model. This work will mainly focus on the multileaf collimator. Also, the codes developed by the group to analyze phase space files produced by MCNP6 have proven highly useful. As work progress and the codes are debugged, they will be published so that the community can take advantage of them.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Persistence and memory timescales in root‐zone soil moisture dynamics

Abstract The memory timescale that characterizes root‐zone soil moisture remains the dominant measure in seasonal forecasts of land‐climate interactions. This memory is a quasi‐deterministic timescale associated with the losses (e.g., evapotranspiration) from the soil column and is often interpreted as persistence in soil moisture states. Persistence, however, represents a distribution of time periods where soil moisture resides above or below some prescribed threshold and is therefore inherently probabilistic. Using multiple soil moisture data sets collected at high resolution (subhourly) across different biomes and climates, this paper explores the differences, underlying dynamics, and relative importance of memory and persistence timescales in root‐zone soil moisture. A first‐order Markov process, commonly used to interpret soil moisture fluctuations derived from climate simulations, is also used as a reference model. Persistence durations of soil moisture below the plant water‐stress level (chosen as the threshold), and the temporal spectrum of upcrossings and downcrossings of this threshold, are compared to the memory timescale and spectrum of the full time series, respectively. The results indicate that despite the differences between meteorological drivers, the spectrum of threshold‐crossings is similar across sites, and follows a unique relation with that of the full soil moisture series. The distribution of persistence times exhibits an approximate stretched exponential type and reflects a likelihood of exceeding the memory at all sites. However, the rainfall counterpart of these distributions shows that persistence of dry atmospheric periods is less likely at sites with long soil moisture memory. The cluster exponent, a measure of the density of threshold‐crossings in a time frame, reveals that the clustering tendency in rainfall events (on‐off switches) does not translate directly to clustering in soil moisture. This is particularly the case in climates where rainfall and evapotranspiration are out of phase, resulting in less ordered (more independent) persistence in soil moisture than in rainfall.

Ghannam, Khaled↗