Belgian Nuclear Research Centre

Core Ideas A community effort is needed to move soil modeling forward. Establishing an international soil modeling consortium is key in this respect. There is a need to better integrate existing knowledge in soil models. Integration of data and models is a key challenge in soil modeling. The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate‐change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

A general description of the mathematical and numerical formulations used in modern numerical reactive transport codes relevant for subsurface environmental simulations is presented. The formulations are followed by short descriptions of commonly used and available subsurface simulators that consider continuum representations of flow, transport, and reactions in porous media. These formulations are applicable to most of the subsurface environmental benchmark problems included in this special issue. The list of codes described briefly here includes PHREEQC, HPx, PHT3D, OpenGeoSys (OGS), HYTEC, ORCHESTRA, TOUGHREACT, eSTOMP, HYDROGEOCHEM, CrunchFlow, MIN3P, and PFLOTRAN. The descriptions include a high-level list of capabilities for each of the codes, along with a selective list of applications that highlight their capabilities and historical development.

Cardis, E., Vrijheid, M., Blettner, M., Gilbert, E., Hakama, M., Hill, C., Howe, G., Kaldor, J., Muirhead, C. R., Schubauer-Berigan, M., Yoshimura, T., Bermann, F., Cowper, G., Fix, J., Hacker, C., Heinmiller, B., Marshall, M., Thierry-Chef, I., Utterback, D., Ahn, Y-O., Amoros, E., Ashmore, P., Auvinen, A., Bae, J-M., Bernar, J. S., Biau, A., Combalot, E., Deboodt, P., Diez Sacristan, A., Eklöf, M., Engels, H., Engholm, G., Gulis, G., Habib, R. R., Holan, K., Hyvonen, H., Kerekes, A., Kurtinaitis, J., Malker, H., Martuzzi, M., Mastauskas, A., Monnet, A., Moser, M., Pearce, M. S., Richardson, D. B., Rodriguez-Artalejo, F., Rogel, A., Tardy, H., Telle-Lamberton, M., Turai, I., Usel, M. and Veress, K. The 15-Country Collaborative Study of Cancer Risk among Radiation Workers in the Nuclear Industry: Estimates of Radiation-Related Cancer Risks. Radiat. Res. 167, 396– 416 (2007).A 15-Country collaborative cohort study was conducted to provide direct estimates of cancer risk following protracted low doses of ionizing radiation. Analyses included 407,391 nuclear industry workers monitored individually for external radiation and 5.2 million person-years of follow-up. A significant association was seen between radiation dose and all-cause mortality [excess relative risk (ERR) 0.42 per Sv, 90% CI 0.07, 0.79; 18,993 deaths]. This was mainly attributable to a dose-related increase in all cancer mortality (ERR/Sv 0.97, 90% CI 0.28, 1.77; 5233 deaths). Among 31 specific types of malignancies studied, a significant association was found for lung cancer (ERR/Sv 1.86, 90% CI 0.49, 3.63; 1457 deaths) and a borderline significant (P = 0.06) association for multiple myeloma (ERR/Sv 6.15, 90% CI <0, 20.6; 83 deaths) and ill-defined and secondary cancers (ERR/Sv 1.96, 90% CI −0.26, 5.90; 328 deaths). Stratification on duration of employment had a large effect on the ERR/Sv, reflecting a strong healthy worker survivor effect in these cohorts. This is the largest analytical epidemiological study of the effects of low-dose protracted exposures to ionizing radiation to date. Further studies will be important to better assess the role of tobacco and other occupational exposures in our risk estimates.

Abstract The joint evaluated fission and fusion nuclear data library 3.3 is described. New evaluations for neutron-induced interactions with the major actinides $$^{235}\hbox {U}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msup><mml:mrow/><mml:mn>235</mml:mn></mml:msup><mml:mtext>U</mml:mtext></mml:mrow></mml:math> , $$^{238}\hbox {U}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msup><mml:mrow/><mml:mn>238</mml:mn></mml:msup><mml:mtext>U</mml:mtext></mml:mrow></mml:math> and $$^{239}\hbox {Pu}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msup><mml:mrow/><mml:mn>239</mml:mn></mml:msup><mml:mtext>Pu</mml:mtext></mml:mrow></mml:math> , on $$^{241}\hbox {Am}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msup><mml:mrow/><mml:mn>241</mml:mn></mml:msup><mml:mtext>Am</mml:mtext></mml:mrow></mml:math> and $$^{23}\hbox {Na}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msup><mml:mrow/><mml:mn>23</mml:mn></mml:msup><mml:mtext>Na</mml:mtext></mml:mrow></mml:math> , $$^{59}\hbox {Ni}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msup><mml:mrow/><mml:mn>59</mml:mn></mml:msup><mml:mtext>Ni</mml:mtext></mml:mrow></mml:math> , Cr, Cu, Zr, Cd, Hf, W, Au, Pb and Bi are presented. It includes new fission yields, prompt fission neutron spectra and average number of neutrons per fission. In addition, new data for radioactive decay, thermal neutron scattering, gamma-ray emission, neutron activation, delayed neutrons and displacement damage are presented. JEFF-3.3 was complemented by files from the TENDL project. The libraries for photon, proton, deuteron, triton, helion and alpha-particle induced reactions are from TENDL-2017. The demands for uncertainty quantification in modeling led to many new covariance data for the evaluations. A comparison between results from model calculations using the JEFF-3.3 library and those from benchmark experiments for criticality, delayed neutron yields, shielding and decay heat, reveals that JEFF-3.3 performes very well for a wide range of nuclear technology applications, in particular nuclear energy.

The ability of many bacteria to adhere to surfaces and to form biofilms has major implications in a variety of industries including the food industry, where biofilms create a persistent source of contamination. The formation of a biofilm is determined not only by the nature of the attachment surface, but also by the characteristics of the bacterial cell and by environmental factors. This review focuses on the features of the bacterial cell surface such as flagella, surface appendages and polysaccharides that play a role in this process, in particular for bacteria linked to food-processing environments. In addition, some aspects of the attachment surface, biofilm control and eradication will be highlighted.

Scientific understanding of any kind of radiation effects starts from the primary damage, i.e. the defects that are produced right after an initial atomic displacement event initiated by a high-energy particle. In this Review, we consider the extensive experimental and computer simulation studies that have been performed over the past several decades on what the nature of the primary damage is. We review both the production of crystallographic or topological defects in materials as well as radiation mixing, i.e. the process where atoms in perfect crystallographic positions exchange positions with other ones in non-defective positions. All classes of materials except biological materials are considered. We also consider the recent effort to provide alternatives to the current international standard for quantifying this energetic particle damage, the Norgett-Robinson-Torrens displacements per atom (NRT-dpa) model for metals. We present in detail new complementary displacement production estimators (“athermal recombination corrected dpa”, arc-dpa) and atomic mixing (“replacements per atom”, rpa) functions that extend the NRT-dpa, and discuss their advantages and limitations.

OBJECTIVES: To provide direct estimates of risk of cancer after protracted low doses of ionising radiation and to strengthen the scientific basis of radiation protection standards for environmental, occupational, and medical diagnostic exposures. DESIGN: Multinational retrospective cohort study of cancer mortality. SETTING: Cohorts of workers in the nuclear industry in 15 countries. PARTICIPANTS: 407 391 workers individually monitored for external radiation with a total follow-up of 5.2 million person years. MAIN OUTCOME MEASUREMENTS: Estimates of excess relative risks per sievert (Sv) of radiation dose for mortality from cancers other than leukaemia and from leukaemia excluding chronic lymphocytic leukaemia, the main causes of death considered by radiation protection authorities. RESULTS: The excess relative risk for cancers other than leukaemia was 0.97 per Sv, 95% confidence interval 0.14 to 1.97. Analyses of causes of death related or unrelated to smoking indicate that, although confounding by smoking may be present, it is unlikely to explain all of this increased risk. The excess relative risk for leukaemia excluding chronic lymphocytic leukaemia was 1.93 per Sv (< 0 to 8.47). On the basis of these estimates, 1-2% of deaths from cancer among workers in this cohort may be attributable to radiation. CONCLUSIONS: These estimates, from the largest study of nuclear workers ever conducted, are higher than, but statistically compatible with, the risk estimates used for current radiation protection standards. The results suggest that there is a small excess risk of cancer, even at the low doses and dose rates typically received by nuclear workers in this study.

The endothelium, a tissue that forms a single layer of cells lining various organs and cavities of the body, especially the heart and blood as well as lymphatic vessels, plays a complex role in vascular biology. It contributes to key aspects of vascular homeostasis and is also involved in pathophysiological processes, such as thrombosis, inflammation, and hypertension. Epidemiological data show that high doses of ionizing radiation lead to cardiovascular disease over time. The aim of this review is to summarize the current knowledge on endothelial cell activation and dysfunction after ionizing radiation exposure as a central feature preceding the development of cardiovascular diseases.

Abstract X-ray computed tomography (CT) is a non-destructive technique with wide applications in various geological disciplines. It reveals the internal structure of objects, determined by variations in density and atomic composition. Large numbers of parallel 2D sections can be obtained, which allows 3D imaging of selected features. Important applications are the study of porosity and fluid flow, applied to investigations in the fields of petroleum geology, rock mechanics and soil science. Expected future developments include the combined use of CT systems with different resolutions, the wider use of related X-ray techniques and the integration of CT data with results of compatible non-destructive techniques.

Nations using borosilicate glass as an immobilization material for radioactive waste have reinforced the importance of scientific collaboration to obtain a consensus on the mechanisms controlling the long-term dissolution rate of glass. This goal is deemed to be crucial for the development of reliable performance assessment models for geological disposal. The collaborating laboratories all conduct fundamental and/or applied research using modern materials science techniques. This paper briefly reviews the radioactive waste vitrification programs of the six participant nations and summarizes the current state of glass corrosion science, emphasizing the common scientific needs and justifications for on-going initiatives.

In this review paper, we present radiation effects on silica-based optical fibers. We first describe the mechanisms inducing microscopic and macroscopic changes under irradiation: radiation-induced attenuation, radiation-induced emission and compaction. We then discuss the influence of various parameters related to the optical fiber, to the harsh environments and to the fiber-based applications on the amplitudes and kinetics of these changes. Then, we focus on advances obtained over the last years. We summarize the main results regarding the fiber vulnerability and hardening to radiative constraints associated with several facilities such as Megajoule class lasers, ITER, LHC, nuclear power plants or with space applications. Based on the experience gained during these projects, we suggest some of the challenges that will have to be overcome in the near future to allow a deeper integration of fibers and fiber-based sensors in radiative environments.

Transposable elements (TE), small mobile genetic elements unable to exist independently of the host genome, were initially believed to be exclusively deleterious genomic parasites. However, it is now clear that they play an important role as bacterial mutagenic agents, enabling the host to adapt to new environmental challenges and to colonize new niches. This review focuses on the impact of insertion sequences (IS), arguably the smallest TE, on bacterial genome plasticity and concomitant adaptability of phenotypic traits, including resistance to antibacterial agents, virulence, pathogenicity and catabolism. The direct consequence of IS transposition is the insertion of one DNA sequence into another. This event can result in gene inactivation as well as in modulation of neighbouring gene expression. The latter is usually mediated by de-repression or by the introduction of a complete or partial promoter located within the element. Furthermore, transcription and transposition of IS are affected by host factors and in some cases by environmental signals offering the host an adaptive strategy and promoting genetic variability to withstand the environmental challenges.

Ralstonia metallidurans, formerly known as Alcaligenes eutrophus and thereafter as Ralstonia eutropha, is a beta-Proteobacterium colonizing industrial sediments, soils or wastes with a high content of heavy metals. The type strain CH34 carries two large plasmids (pMOL28 and pMOL30) bearing a variety of genes for metal resistance. A chronological overview describes the progress made in the knowledge of the plasmid-borne metal resistance mechanisms, the genetics of R. metallidurans CH34 and its taxonomy, and the applications of this strain in the fields of environmental remediation and microbial ecology. Recently, the sequence draft of the genome of R. metallidurans has become available. This allowed a comparison of these preliminary data with the published genome data of the plant pathogen Ralstonia solanacearum, which harbors a megaplasmid (of 2.1 Mb) carrying some metal resistance genes that are similar to those found in R. metallidurans CH34. In addition, a first inventory of metal resistance genes and operons across these two organisms could be made. This inventory, which partly relied on the use of proteomic approaches, revealed the presence of numerous loci not only on the large plasmids pMOL28 and pMOL30 but also on the chromosome. It suggests that metal-resistant Ralstonia, through evolution, are particularly well adapted to the harsh environments typically created by extreme anthropogenic situations or biotopes.

High-throughput amplicon sequencing has become a well-established approach for microbial community profiling. Correlating shifts in the relative abundances of bacterial taxa with environmental gradients is the goal of many microbiome surveys. As the abundances generated by this technology are semi-quantitative by definition, the observed dynamics may not accurately reflect those of the actual taxon densities. We combined the sequencing approach (16S rRNA gene) with robust single-cell enumeration technologies (flow cytometry) to quantify the absolute taxon abundances. A detailed longitudinal analysis of the absolute abundances resulted in distinct abundance profiles that were less ambiguous and expressed in units that can be directly compared across studies. We further provide evidence that the enrichment of taxa (increase in relative abundance) does not necessarily relate to the outgrowth of taxa (increase in absolute abundance). Our results highlight that both relative and absolute abundances should be considered for a comprehensive biological interpretation of microbiome surveys.

Atomic collision processes are fundamental to numerous advanced materials technologies such as electron microscopy, semiconductor processing and nuclear power generation. Extensive experimental and computer simulation studies over the past several decades provide the physical basis for understanding the atomic-scale processes occurring during primary displacement events. The current international standard for quantifying this energetic particle damage, the Norgett-Robinson-Torrens displacements per atom (NRT-dpa) model, has nowadays several well-known limitations. In particular, the number of radiation defects produced in energetic cascades in metals is only ~1/3 the NRT-dpa prediction, while the number of atoms involved in atomic mixing is about a factor of 30 larger than the dpa value. Here we propose two new complementary displacement production estimators (athermal recombination corrected dpa, arc-dpa) and atomic mixing (replacements per atom, rpa) functions that extend the NRT-dpa by providing more physically realistic descriptions of primary defect creation in materials and may become additional standard measures for radiation damage quantification.

Abstract Probabilistic inversion within a multiple‐point statistics framework is often computationally prohibitive for high‐dimensional problems. To partly address this, we introduce and evaluate a new training‐image based inversion approach for complex geologic media. Our approach relies on a deep neural network of the generative adversarial network (GAN) type. After training using a training image (TI), our proposed spatial GAN (SGAN) can quickly generate 2‐D and 3‐D unconditional realizations. A key characteristic of our SGAN is that it defines a (very) low‐dimensional parameterization, thereby allowing for efficient probabilistic inversion using state‐of‐the‐art Markov chain Monte Carlo (MCMC) methods. In addition, available direct conditioning data can be incorporated within the inversion. Several 2‐D and 3‐D categorical TIs are first used to analyze the performance of our SGAN for unconditional geostatistical simulation. Training our deep network can take several hours. After training, realizations containing a few millions of pixels/voxels can be produced in a matter of seconds. This makes it especially useful for simulating many thousands of realizations (e.g., for MCMC inversion) as the relative cost of the training per realization diminishes with the considered number of realizations. Synthetic inversion case studies involving 2‐D steady state flow and 3‐D transient hydraulic tomography with and without direct conditioning data are used to illustrate the effectiveness of our proposed SGAN‐based inversion. For the 2‐D case, the inversion rapidly explores the posterior model distribution. For the 3‐D case, the inversion recovers model realizations that fit the data close to the target level and visually resemble the true model well.

Since a corrosion process is a nonlinear electrochemical phenomenon, a potential perturbation signal by one or more sine waves will generate current responses at more frequencies than the frequencies of the applied signal. Current responses can then be measured, for example, at zero, harmonic, and intermodulation frequencies. This simple principle offers various possibilities for corrosion rate measurements, like the intermodulation or electrochemical frequency modulation (EFM) technique in which the potential perturbation signal consists of two sine waves of different frequencies. With this novel EFM technique, the corrosion rate can be determined from the corrosion system responses at the intermodulation frequencies. With the EFM technique a corrosion rate can be obtained instantaneously, without prior knowledge of the so-called Tafel parameters. The EFM approach requires only a small polarizing signal, and measurements can be completed in a short period. A special advantage of the EFM technique is its capability of inherent data validation control using “causality factors” (parameters introduced for the first time in this paper). It is shown that the EFM technique can be used successfully for corrosion rate measurements under various corrosion conditions, such as mild steel in an acidic environment with and without inhibitors and mild steel in a neutral environment.

Abstract. Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming industry applications and generating new and improved capabilities for scientific discovery and model building. The adoption of DL in hydrology has so far been gradual, but the field is now ripe for breakthroughs. This paper suggests that DL-based methods can open up a complementary avenue toward knowledge discovery in hydrologic sciences. In the new avenue, machine-learning algorithms present competing hypotheses that are consistent with data. Interrogative methods are then invoked to interpret DL models for scientists to further evaluate. However, hydrology presents many challenges for DL methods, such as data limitations, heterogeneity and co-evolution, and the general inexperience of the hydrologic field with DL. The roadmap toward DL-powered scientific advances will require the coordinated effort from a large community involving scientists and citizens. Integrating process-based models with DL models will help alleviate data limitations. The sharing of data and baseline models will improve the efficiency of the community as a whole. Open competitions could serve as the organizing events to greatly propel growth and nurture data science education in hydrology, which demands a grassroots collaboration. The area of hydrologic DL presents numerous research opportunities that could, in turn, stimulate advances in machine learning as well.

Many bacteria in the environment have adapted to the presence of toxic heavy metals. Over the last 30 years, this heavy metal tolerance was the subject of extensive research. The bacterium Cupriavidus metallidurans strain CH34, originally isolated by us in 1976 from a metal processing factory, is considered a major model organism in this field because it withstands milli-molar range concentrations of over 20 different heavy metal ions. This tolerance is mostly achieved by rapid ion efflux but also by metal-complexation and -reduction. We present here the full genome sequence of strain CH34 and the manual annotation of all its genes. The genome of C. metallidurans CH34 is composed of two large circular chromosomes CHR1 and CHR2 of, respectively, 3,928,089 bp and 2,580,084 bp, and two megaplasmids pMOL28 and pMOL30 of, respectively, 171,459 bp and 233,720 bp in size. At least 25 loci for heavy-metal resistance (HMR) are distributed over the four replicons. Approximately 67% of the 6,717 coding sequences (CDSs) present in the CH34 genome could be assigned a putative function, and 9.1% (611 genes) appear to be unique to this strain. One out of five proteins is associated with either transport or transcription while the relay of environmental stimuli is governed by more than 600 signal transduction systems. The CH34 genome is most similar to the genomes of other Cupriavidus strains by correspondence between the respective CHR1 replicons but also displays similarity to the genomes of more distantly related species as a result of gene transfer and through the presence of large genomic islands. The presence of at least 57 IS elements and 19 transposons and the ability to take in and express foreign genes indicates a very dynamic and complex genome shaped by evolutionary forces. The genome data show that C. metallidurans CH34 is particularly well equipped to live in extreme conditions and anthropogenic environments that are rich in metals.

Since the ITER divertor design includes tungsten monoblocks in the vertical target where heat loads are maximal, the design to protect leading edges as well as technology R&amp;D for high performance armor-heat sink joint were necessary to be implemented. In the R&amp;D, the availability of the technology was demonstrated by high heat flux test of tungsten monoblock components. Not systematically but frequently macro-cracks appeared at the middle of monoblocks after 20 MW/m2 loading. The initiation of such macro-cracks was considered to be due to cyclic exposure to high temperature, ∼2000 °C, where creep, recrystallization and low cycle fatigue were concerned. To understand correlation between the macro-crack appearance and mechanical properties and possible update of acceptance criteria in the material specification, an activity to characterize the tungsten monoblocks was launched.