Light Water Research Articles

Effects of the Water Diversion Project from the Three Gorges Reservoir to the Hanjiang River on diatom blooms in Middle and Lower reaches of the Hanjiang River

ABSTRACT The algal blooms in the Middle and Lower reaches of the Hanjiang River (MLHR) have become a great aquatic eco-environmental problem over recent years. The planned implementation of the Water Diversion Project from the Three Gorges Reservoir to the Hanjiang River (WDP-TH) would influence the growth and propagation of diatoms and the development of algal blooms. In this paper, a dynamic model of diatom growth is developed that considers factors such as light exposure, water temperature, total phosphorus, and flow velocity. The effects of the WDP-TH on algal density and blooms in the MLHR were predicted for a typical median year, a typical dry year, and an extremely dry year. The results showed that following the water recharge in a typical median year, the propagation of diatoms in the MLHR was significantly promoted because of an increase in total phosphorus concentration. However, following the water recharge in typical dry and extremely dry years, increased flow rate and improved hydrodynamic conditions significantly inhibited diatom growth and accelerated the transport process. The results of the hypothetical simulation showed that after the initiation of the WDP-TH, inhibition effects of improved hydrodynamic force on algae were more apparent than promotion effects of increased total phosphorus concentration in the MLHR.

ARIANT Assessments for CANDU Analysis Using RD-14M Experiments

ARIANT (AlgoRIthm for Analysis of Network Thermalhydraulics) is a Canadian Nuclear Laboratories system thermal-hydraulic code for the modeling and analysis of two-phase flow and heat transfer for pressurized heavy water reactors, light water pressurized water reactors, and advanced reactor applications. This paper presents ARIANT models and simulations of RD-14M experiments, including small-break loss-of-coolant accidents, large-break loss-of-coolant accidents, loss-of-flow accidents, station blackout, and natural circulation, that are representative of accident scenarios in a CANDU reactor. ARIANT predictions of pressures, flow rates, temperatures, and void fractions are compared against the steady-state and transient data over the course of the tests. The results show that ARIANT predicted the key parameters with reasonable accuracy, as well as the overall behavior of the five transient events. These assessments support ARIANT’s applicability to the corresponding CANDU design-basis accidents and demonstrate ARIANT as an alternative to existing system thermal-hydraulic codes for CANDU safety analysis.

Chemical interaction of CsOH vapor with UO2 and Fe-Zr melt

ABSTRACT At TEPCO’s Fukushima Daiichi Nuclear Power Station, it is estimated that considerable amounts of cesium still remain in the reactors from the analysis results using the severe accident analysis codes and the reverse analysis from contaminated water. Since cesium is known to form stable compounds with uranium and zirconium, chemisorption experiments with uranium dioxide pellets and iron-zirconium melts for cesium hydroxide vapor were carried out using the similar method as for stainless steel. As the results, formations of cesium uranate, Cs2UO4, and cesium zirconate, Cs2ZrO3, were confirmed, indicating that cesium was chemisorbed on both of the uranium dioxide pellets and the iron-zirconium melts in an Ar-H2-H2O flow and an Ar-H2 flow, respectively. Therefore, it was considered that cesium released from fuel might be trapped by chemisorption with fuels and/or iron-zirconium melts during light water reactor severe accidents.

Attenuated total reflection Fourier-transform infrared spectroscopy reveals environment specific phenotypes in clonal Japanese knotweed

BackgroundJapanese knotweed (Reynoutria japonica var. japonica), a problematic invasive species, has a wide geographical distribution. We have previously shown the potential for attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy and chemometrics to segregate regional differentiation between Japanese knotweed plants. However, the contribution of environment to spectral differences remains unclear. Herein, the response of Japanese knotweed to varied environmental habitats has been studied. Eight unique growth environments were created by manipulation of the red: far-red light ratio (R: FR), water availability, nitrogen, and micronutrients. Their impacts on plant growth, photosynthetic parameters, and ATR-FTIR spectral profiles, were explored using chemometric techniques, including principal component analysis (PCA), linear discriminant analysis, support vector machines (SVM) and partial least squares regression. Key wavenumbers responsible for spectral differences were identified with PCA loadings, and molecular biomarkers were assigned. Partial least squared regression (PLSR) of spectral absorbance and root water potential (RWP) data was used to create a predictive model for RWP.ResultsSpectra from plants grown in different environments were differentiated using ATR-FTIR spectroscopy coupled with SVM. Biomarkers highlighted through PCA loadings corresponded to several molecules, most commonly cell wall carbohydrates, suggesting that these wavenumbers could be consistent indicators of plant stress across species. R: FR most affected the ATR-FTIR spectra of intact dried leaf material. PLSR prediction of root water potential achieved an R2 of 0.8, supporting the potential use of ATR-FTIR spectrometers as sensors for prediction of plant physiological parameters.ConclusionsJapanese knotweed exhibits environmentally induced phenotypes, indicated by measurable differences in their ATR-FTIR spectra. This high environmental plasticity reflected by key biomolecular changes may contribute to its success as an invasive species. Light quality (R: FR) appears critical in defining the growth and spectral response to environment. Cross-species conservation of biomarkers suggest that they could function as indicators of plant-environment interactions including abiotic stress responses and plant health.

Demulsification of water in crude oil emulsions via phosphonium-based ionic liquids: Statistical modeling and optimization

In the present study, the performance of two ionic liquids namely Tetrabutylphosphonium bromide (TBPB) and Tetraoctylphosphonium bromide (TOPB) as the demulsifying compounds are investigated in the demulsification operation of water in light and medium crude oil emulsions for the first time. The response surface methodology (RSM) is employed to evaluate the impact of temperature, pH, water content, demulsifier concentration, and settling time on the demulsification efficiencies of studied demulsifiers. In order to design the requisite experiments and optimize the effective factors on the water removal efficiency, the central composite design (CCD) is applied. To determine the optimal conditions of input parameters, four exact models are created by utilizing the responses of 184 experiments to predict the demulsification efficiencies of two demulsifiers for two types of crude oils based on statistical tests of different models using the analysis of variance (ANOVA). High R2 coefficient values imply that the developed models could reproduce the experimental results of the studied demulsifiers appropriately. At the optimal conditions, the water in light and medium crude oil emulsions are completely broken in the samples containing TOPB. Moreover, TBPB agent presents high and acceptable demulsification efficiencies for both types of crude oils at the optimal values of process parameters i.e. 98.078% and 96.025% for light and medium crude oil emulsions, respectively. The superior demulsification performance of TOPB with respect to TBPB can be ascribed to the longer alkyl chain length of TOPB.

Investigation of the Thermal Effects of MgO and ZnO Nanoparticles in a Pressurized Water Reactor Coolant with Computational Fluid Dynamics Model

When nanofluids are used as reactor coolants, they provide more effective heat transfer with their increase in thermal conduction properties. This plays an important role in energy production by increasing the efficiency of nuclear reactors. The present study delves into the thermal-hydraulic ramifications of utilizing nanofluids as coolants in the VVER-1000 nuclear reactor. Specifically, the thermal-hydraulic characteristics, encompassing parameters such as coolant temperature and departure from nucleate boiling ratio, were scrutinized in light of the incorporation of magnesium oxide (MgO) and zinc oxide nanoparticles. While performing these analyses, not only uranium but also thorium was used in the core as reactor fuel. Considering the emergence of thorium as a potential fuel material in nuclear technology, its inclusion in the fuel composition contributed to the originality of the research. With the addition of 0.2% MgO nanoparticles to a VVER nuclear reactor using 5% thorium dioxide (ThO2) fuel, the coolant temperature as a result of the channel flow was determined as 617.4 K (while 613.7 K for the light water). When employing thorium fuel (with an equivalent nanoparticle concentration), the maximum temperature exhibited an approximate increase of 3 deg compared to uranium fuel. With the addition of 0.2% MgO nanoparticles, the enthalpy value at the end of the channel was 1303.6 kJ/kg when using 5% ThO2 fuel, while the enthalpy value was determined as 1295 kJ/kg in 3.7% enriched UO2 fuel. As one of the most important results of the analysis, it was observed that the temperature value of the coolant increased when nanoparticles were used.

Light reduction and watering enhance flora memory awakening after forest topsoil translocation

Plant propagules are crucial flora memory materials in restoration practice. Awakening flora memory from plant propagules (i.e. seeds, root fragments, rhizomes, corms, and tubers) in the translocated topsoil from a donor site is a rapid method for forest restoration on degraded sites globally. However, it remains unclear to what extent manageable measures, such as light reduction and watering, affect flora memory awakening. We employed a quadratic saturation D‐optimal design in a forest topsoil translocation experiment to quantify the effects of light reduction and watering on flora memory awakening. We used the cumulative number and richness of plantlets emerging from plant propagules to represent the extent of flora memory awakening. Our results show that any combinations of light reduction and watering significantly increased both the cumulative number and richness of plantlets across different life forms. Light reduction had a significantly more positive effect on flora memory awakening than watering. Different life forms exhibited different parabolic or positive linear relationships in responses to light reduction and watering. Light reduction of about 60% of the degraded site and watering of about 80% of the donor site resulted in the highest number and richness of plantlets. We concluded that light reduction and watering combinations were effective in kick‐starting the flora memory awakening in a semiarid subtropical forest after topsoil translocation.

Radiation induced athermal diffusivity in uranium mononitride

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuel considered for light water reactors and advanced reactor designs. Properties like self- and fission gas diffusivity need to be better understood, given that they influence key fuel performance phenomena such as fission gas swelling and release. In particular, the radiation induced athermal (D3) diffusivity remains challenging to accurately predict and has only been sparsely characterized in UN, despite its importance as it likely governs diffusion at the low temperatures this high-thermal-conductivity fuel form may operate. Molecular Dynamics simulations are used to estimate the mean square displacement induced by a primary knock-on atom (PKA) with a given kinetic energy. These results are combined with the PKA energy distributions obtained from binary collision approximation calculations to obtain the displacement due to a particular fission fragment. Finally, this is combined with experimental fission fragment yields to determine the displacement due to an average fission event and, thus, express the athermal diffusivity as a function of the fission rate density. These results are in excellent agreement with available experimental data. A particular importance is given to the understanding and the quantification of the variability of these results.

Effect of initial microstructure on irradiation induced microstructure evolution in δ-ferrite in an austenitic stainless steel weld

The irradiation induced microstructure evolution of δ-ferrite in an austenitic stainless steel weld was investigated. To simulate long-term service in light water reactor (LWR) at operating temperature, accelerated thermal aging at 400 °C up to 30,000 h was performed. Then, proton irradiation up to 10 displacement per atom (dpa) was subsequently conducted for unaged and aged samples. For the unaged samples, formation of Cr-rich (α’) phase by spinodal decomposition increased with irradiation dose. Meanwhile, formation of G-phase was promoted after 1 dpa, but decreased after 10 dpa. For the aged samples, after 1 dpa irradiation, Cr-rich (α’) phase formed by spinodal decomposition during thermal aging was destroyed while population of G-phase increased. After further irradiation up to 10 dpa, α’ phase was re-precipitated and coarsened significantly, but the degree of which was significantly less compared to the unaged samples. Meanwhile, with increase of irradiation to 10 dpa, G-phase population increased for the aged samples. The difference in the evolution of microstructural features during irradiation were discussed in view of the initial microstructure of δ-ferrite.

Internet of things-based rice field irrigation evaporation monitoring system

The urgency for efficient irrigation in Indonesia’s agriculture sector, particularly in paddy fields, is evident. However, existing methods for monitoring water levels are antiquated, often requiring manual measurements with a ruler. This research introduces a comprehensive “monitoring system for light intensity and water temperature as an analysis of evaporation for rice irrigation based on the internet of things”. The system integrates various sensors an anemometer for wind speed, an ultrasonic sensor for water level, a DS18B20 waterproof sensor for water temperature, and a GY-8511 sensor for sunlight intensity. All data are collected by an Arduino Mega controller, connected to an ESP32 for transmitting the readings to the Blynk app and an I2C 20×4 liquid crystal display (LCD) screen. The control mechanism employs a closed-loop system with a direct current (DC) motor actuator to operate the water gate, which can also be manually controlled via a cellphone. The system effectively meets daily evapotranspiration requirements of 1.44 mm, with optimal conditions yielding water levels of 3 cm, water temperatures of 38.53 °C, sunlight intensity of 4.59 mW/cm², and wind speed of 0.21 m/s.

Thermodynamic study on the separation of strontium and barium from LWR spent fuel

The separation of high heat load fission products, such as alkaline earth metals, from nuclear spent fuel can significantly reduce the burden of spent fuel disposal. This study investigates the feasibility of separating strontium and barium from light water reactor spent fuel through non-aqueous processes. Process flows were developed for treating spent nuclear fuel by heating it at high temperatures to remove volatile nuclides, followed by chlorination with a chlorinating agent. The chlorinated products were then treated with a precipitating agent in LiCl-KCl molten salt for further separation. The remaining liquid was distilled to recover strontium and barium. Thermodynamic equilibrium calculations were conducted for the process flows. Under the conditions of the process flows, the chlorinating agents MgCl2 and NH4Cl both converted SrO and BaO entirely into SrCl2 and BaCl2, respectively. The precipitating agent Li2CO3 exhibited superior separation effectiveness compared to Li3PO4. Thermodynamic calculations indicate that strontium and barium recovered by MgCl2 chlorination, Li2CO3 precipitation, and distillation will contain 0.18 %, 1.06 %, and 0.32 % impurities in terms of mass, radioactivity, and decay heat, respectively.

Integral-scale validation of the SCIANTIX code for Light Water Reactor fuel rods

Mechanistic multi-scale modelling holds the potential to inform fuel performance codes by incorporating high-fidelity models, algorithms, parameters, and material properties. In this context, meso-scale codes emerge as valuable tools for developing detailed models and performing separate verification and validation steps. This work focuses on SCIANTIX, an open-source 0D meso-scale code designed to describe the behaviour of gaseous and volatile fission products in nuclear oxide fuel. The code predominantly employs engineering physics-based behavioural models featuring computational times that align with typical fuel performance code requirements. Given the numerical foundation of the code, it is applicable to both stationary and transient conditions. Following a recent work outlining the standalone SCIANTIX (version 2.0) performance and its separate-effect validation database, we present its performance when coupled with fuel performance codes to simulate light water reactor fuel rods. The experiments selected for the comparative analysis constitute an initial integral validation database. The comparison focuses on conventional engineering quantities of interest, such as integral fission gas release, demonstrating the satisfactory performance of the code. Additionally, it highlights the potential advantages of multi-scale modelling over conventional semi-empirical approaches.

Systematic evaluations and integration of Assam indigenous Joha rice starch in intelligent packaging films for monitoring food freshness using beetroot extract

It is becoming increasingly important to have starch sources with different physicochemical properties to meet the needs of new applications in food, packaging, bioplastic, and pharmaceutical industries. The first part of this study dealt with the isolation of starch from culturally, geographically, nutritionally esteemed, and high-yielding Assam Joha rice. Fine and uniform particle size (6.3 ± 0.09 μm), high amylose content (28 ± 1.03 %), swelling behavior, viscoelastic rheological behavior, moderate gelatinization temperature (66 ± 1.7 °C), thermostable nature, type A crystallographic pattern with high (45 ± 3.3 %) crystallinity, and suitable microbial quality make the Joha rice derived starch physico-chemically and functionally suitable for potential applications in diverse domains. The latter part of the study focuses on one of the applications of derived starch as a suitable matrix for intelligent packaging films with the incorporation of betanin-enriched beetroot extract (BRE) as a bio-based pH sensor. The addition of 1.0 % w/v BRE to the starch film (starch-BRE III) significantly increased its functionality by reducing UV–visible light transmittance and water vapor permeability, along with enhancing flexibility and hydrophobicity due to intermolecular bonding between BRE and the starch film matrix. Moreover, starch-BRE films with different BRE concentrations were successfully used to monitor the real-time freshness of white meat (chicken and fish) and Indian cottage cheese samples. Overall, the results indicated that starch-BRE III has great potential as an intelligent packaging material for monitoring food freshness.

RELATIVE IMPORTANCE INDEX OF LEADING INDICATORS FIRE PROTECTION SYSTEMS IN HIGHER EDUCATION BUILDINGS IN KOTA BANDA ACEH

Fire can cause material loss and also cause physical disabilities and even fatalities for building users. Fires that occur as a result of human activity must be overcome by increasing human awareness themselves. However, fires caused by natural factors or errors in the electrical system can be overcome by having a fire prevention system or safety system. The aim of the research is to identify the main indicators of fire protection systems in educational buildings in Banda Aceh City. A closed questionnaire and Likert scale survey of respondents using educational buildings was conducted to collect data. Next, the data is processed using the frequency index analysis method and the Relative Importance Index (RII). The results of the frequency index analysis provide an overview of the percentage level of occurrence of the fire protection system variable, namely the acid detector, at 91.294%. Based on the results of the RII analysis, five main indicators were found that influence the safety system, namely light fire extinguishers (0.929), smoke detectors (0.913), water transmitters (0.911), standpipes (0.894), and fire hydrant systems (0.892). Meanwhile, the main variable for the fire protection system is the active protection system with a RII value of 0.889.

Fuzzy reliability algorithm for the shutdown system of research reactor

Abstract Probabilistic safety assessment (PSA) has been applied to evaluate the safety of nuclear reactor systems. The results of PSA are used by designers, utilities and regulatory body to confirm the reactor design, to change operation procedures, to enhance the reliability of safety systems, or to modify regulation. Fault tree analysis (FTA) has been used as a deductive means for PSA. System components are assumed to always have defined failure probabilities; however, in reality this assumption is questionable and sometimes there is insufficient data about the failure probability of some components. To solve this problem, fuzzy approaches have been proposed and implemented. The aim of this study is to apply a fuzzy reliability algorithm to estimate basic events failure probabilities for the shutdown system of a research reactor. The reactor is a 22 MW light water open pool type material test reactor and the shutdown system is responsible for the fast shutdown of the reactor whenever safety limits are exceeded. Then, to illustrate the ability of the algorithm, the results are compared with real basic event failure probabilities. The results verify the competence of the algorithm and confirm that it can be applied as an alternative method when quantitative data are not available. Also, a risk importance measure is done on the fault tree of the shutdown system to illustrate which components need to be focused for improvements to achieve the safe operation of shutdown system.

Full prediction of band potentials in semiconductor materials

A machine learning (ML) framework to predict the physical band potentials for a range of semiconductor materials, from metal sulfide, oxide, and nitride, to oxysulfide and oxynitride, is hereby described. A valence band maximum (VBM) model was established via the transfer learning of a large dataset of 2D materials (1382 samples, but with incorrect VBM potentials) onto a much smaller dataset of physically measured VBM for bulk 3D materials (87 samples) on a crystal graph convolutional neural network. This resulted in predictions with experimental accuracy (RMSE = 0.27 eV), which is a 3-fold improvement compared with ML trained on the physical dataset without transfer learning (RMSE = 0.75 eV). When combined with the bandgap prediction model (RMSE = 0.29 eV), a full prediction of conduction and valence band potentials can be made, which to the best of our knowledge, is the first for any ML framework. The variation of band potentials across low-index surfaces was predicted correctly and verified with reported physical potentials. In fact, the framework is able to capture variation in band potentials associated with minor atomic position alterations. Based on this, a general trend between surface atomic displacement and VBM shift was observed across various semiconductor materials. The model is not yet able to cope with major rearrangement of atomic sequence on surface layers, i.e., surface reconstructions, since it was not trained with such data but can be easily done so with specifically designed dataset. As an example application, the ML framework was used for the screening of potential photocatalytic materials for visible light water splitting. A total of 824 materials was successfully identified, including those experimentally-verified in the literature.

Analyses of Jet Buoyant Flow in a Multicompartment Containment Using an Open-Source Solver

Hydrogen mixing and distribution in a nuclear power plant containment during a postulated severe accident is a phenomenon with high safety relevance for current and advanced light water reactors. The Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) SESAR Thermal-Hydraulics (SETH) project was carried out to generate experimental data on basic containment phenomena with the required instrumentation to assess computational fluid dynamics (CFD) and lumped parameter codes. In this paper, we analyze the PANDA SETH Test 16 of the OECD/NEA SETH project using containmentFOAM, which is a tailored open-source CFD code package for containment analysis developed at Forschungszentrum Jülich GmbH based on OpenFOAM.® SETH Test 16 addressed steam-air mixture transport driven by jets and plumes in the multicompartment PANDA facility (two vessels and an interconnecting pipe) at the Paul Scherrer Institut in Switzerland. Steam as a wall plume was injected at 0.040 kg/s and 140°C in vessel 1, which was initially filled with dry air at 108°C. The steam-air mixture was vented out from the top of vessel 2. The system pressure was constant at 1.3 bar for the whole test duration (4000 s). To simulate SETH Test 16, the k-ω shear stress transport turbulence model was adopted with the generalized gradient diffusive hypothesis buoyancy turbulence model. The simulation represented the experimental phenomenology reasonably well. The trends for the calculated temperature distribution were similar to those of the experiments and only yielded a slight discrepancy of about 2.7%. In addition, the distribution of the steam molar fraction was well predicted above the injection tube in vessel 1. However, below the injection tube in vessel 1, some discrepancies between the simulations and the experimental results were observed. These may have been caused by the higher turbulent mass diffusivity in the physical model and the challenge of the mesh resolution in the middle region of vessel 1.

Photosynthetic Acclimation of Larch to the Coupled Effects of Light Intensity and Water Deficit in Regions with Changing Water Availability.

The impact of frequent water deficits on dominant tree species in boreal forests has received increased attention, particularly towards addressing the global climate change scenarios. However, the impacts of coupled light intensity and water deficit in the regeneration and growth of Larix gmelinii seedlings, a dominant species in China's boreal forests, are still unclear. We conducted a dual-factor controlled experiment with four light intensities (natural sunlight, 50% shading, 75% shading, and 90% shading) and three soil water conditions (80%, 60%, and 40% soil saturated water content). The results showed that the coupling of light and water has a significant effect on the growth and development of Larix gmelinii seedlings. In 40% of the saturated soil moisture content, net photosynthetic rate, transpiration rate, chlorophyll a, and total phenol-leaf were significantly lower than the same light conditions under 80% soil saturated water content. Under the coupling treatment of 60% soil saturated water content and 50% shading treatment, the plant height increment, net photosynthetic rate, stomatal conductance, transpiration rate, chlorophyll a, and phenolic compound content were significantly higher than those of other coupling treatments; however, more than 75% shading inhibited photosynthetic parameters, chlorophyll a, total flavonoid-leaf, and total flavonoid-branch. Our results have important implications for forest management practices; they provide a scientific reference for the early growth of Larix gmelinii seedlings under the coupling of light and water and promote the survival and growth of seedlings.

Protonated Z-scheme CdS-covalent organic framework heterojunction with highly efficient photocatalytic hydrogen evolution

The low efficiency of photocatalytic hydrogen production from water is mainly suffer from limited light absorption, charge separation and water delivery to the active centers. Herein, an inorganic–organic Z-scheme heterojunction (CdS-COF-Ni) is constructed by in-situ growth of CdS nanosheets on the porphyrin-based covalent organic framework with nickel ions (COF-Ni) in the porphyrin centers. A built-in electric field is formed at the interface, which accelerates the separation and transfer of photogenerated charges. Moreover, through the surface protonation treatment in ascorbic acid (AC) solution, the hydrophilicity of the obtained composite is obviously increased and facilitates the transport of water molecules to the photocatalytic centers. Under the synergistic effect of the interfacial interaction and surface protonation treatment, the photocatalytic hydrogen production rate is optimized to be 18.23 mmol h−1 g−1 without adding any cocatalysts, which is 21 times that of CdS. After a series of photoelectrochemical measurements, in situ X-ray photoelectron spectroscopy (XPS) analysis, and density functional theory (DFT) calculations, it is found that the photocatalytic charge transfer pathway conforms to the Z-scheme mechanism, which not only greatly accelerates the separation and transfer of photogenerated charges, but also retains a high reduction capacity for water splitting. This work offers a good strategy for constructing highly efficient organic–inorganic heterojunctions for water splitting.

Systematic experimental and model-based evaluation of the synergistic effects of alloy composition and damage rate on the formation of Cr-rich precipitates in Fe–Cr–Al alloys under ion irradiation

Fourteen Fe–Cr–Al alloys with systematically varied Cr and Al compositions were irradiated at 350∘C to 0.24 dpa by 10.5 MeV self-ions as model alloys for the Fe–Cr–Al (oxide dispersion strengthened: ODS) alloys being developed as accident tolerant fuel (ATF) cladding for light water reactors. Three dose rates (8×10−6, 8×10−5, and 8×10−4 dpa/s) were selected to predict the formation behavior of Cr-rich precipitates (CrRP) under neutron irradiation conditions. The effects of Cr, Al composition, and dose rate on the CrRP formation behavior were evaluated using a three-dimensional atom probe (3DAP) analysis. The results showed that the CrRP number density, volume fraction, and Cr concentration increase with increasing Cr composition, decreasing Al composition, and decreasing dose rate. Multiple regression analysis showed that in addition to these primary effects, there was an interaction between them on the CrRP volume fraction: (1) the higher the Al composition, the smaller the increase in the CrRP volume fraction with increasing Cr composition, and (2) the lower the Cr composition, the smaller the increase in the CrRP volume fraction with the decreasing Al composition and dose rate. It was also highlighted that to understand the dose rate effect on the CrRP formation behavior under neutron irradiation, it is useful to examine the irradiation time dependence, including the effective use of thermal aging data as a limit to the zero dose rate, in addition to the dose-dependency perspective. In addition to the systematic database of CrRP-related quantities established in this study, these considerations should contribute to further developing and validating numerical prediction models.