WU Xiaoming1, 2, WEN Xuejun2, 3, XUE Yun1, 4, TIAN Guoxin4, LIN Min2, TANG Mingze2, MA Fuqiu1, 4
This study aims to investigate the heterodimeric probe [18F]AlF-labeled targeting both fibroblast activation protein (FAP) and integrin receptor αⅤβ3: 1,4,7-triazacyclononane-1,4,7-triacetic acid-FAP inhibitor-arginine-glycine-aspartic acid (NOTA-FAPI-RGD) for its potential application in small-animal PET imaging of FAP-positive tumor-bearing nude mouse models and its preliminary clinical application. [18F]AlF-NOTA-FAPI-RGD was synthesized using an optimized [18F]AlF-labeling method developed in previous studies. Cellular uptake and blocking experiments were performed in HT1080-FAP tumor cells to evaluate specific uptake in vitro. PET imaging was conducted in HT1080-FAP tumor-bearing mice to observe the distribution of [18F]AlF-NOTA-FAPI-RGD in the HT1080-FAP tumor model. Competitive PET imaging was performed by co-injection of NOTA-FAPI-02, NOTA-RGD, and NOTA-FAPI-RGD inhibitors, respectively, alongside imaging using [18F]AlF-NOTA-FAPI-02 and [18F]AlF-NOTA-RGD, to assess dual-target specificity in vivo. In addition, preliminary clinical PET imaging was also performed in breast cancer patients to evaluate its diagnostic performance. The dual-target radiotracer [18F]AlF-NOTA-FAPI-RGD is successfully synthesized and evaluated in this study. It exhibites significant uptake in HT1080-FAP tumor cells; Cell uptake can reach up to 44.66%±0.26%. After being blocked with NOTA-FAPI-02, NOTA-RGD, and NOTA-FAPI-RGD inhibitors, the cell uptake decreases to 0.46%±0.04%, 37.61%±1.21%, and 0.16%±0.02%, with P<0.01, which confirms the dual-target specificity of [18F]AlF-NOTA-FAPI-RGD. In HT1080-FAP tumor-bearing mice, PET imaging demonstrates that [18F]AlF-NOTA-FAPI-RGD displays excellent pharmacokinetics, with high tumor uptake and prolonged retention time: Tumor uptake can reach up to (9.67±1.23)%ID/g at 0.5 h, and 6 h post-injection, tumor uptake still retains (8.10±1.35)%ID/g. Tumor uptake is effectively inhibited by NOTA-FAPI-02, NOTA-RGD, and NOTA-FAPI-RGD inhibitors, which demonstrates the dual-targeting specificity for both FAP and integrin receptor αⅤβ3. In contrast, the control radiotracers [18F]AlF-NOTA-FAPI-02 and [18F]AlF-NOTA-RGD show lower HT1080-FAP tumor uptake and retention, which indicates the superiority of [18F]AlF-NOTA-FAPI-RGD. Furthermore, clinical PET imaging in breast cancer patients demonstrates a greater lesion uptake value for [18F]AlF-NOTA-FAPI-RGD (SUVmax=12.41) compared to [18F]FDG (SUVmax=7.45). [18F]AlF-NOTA-FAPI-RGD demonstrates dual-targeting specificity for both FAP and integrin receptor αⅤβ3, as well as high tumor uptake and prolonged tumor retention in both preclinical and clinical studies. Compared to single-targeting tracers, it shows superior imaging quality and lesion detection. These results highlight the potential of [18F]AlF-NOTA-FAPI-RGD as a radiotracer for diagnosing tumors with high FAP and/or integrin αⅤβ3 expression, which offers promising prospects for clinical application.
Classic problem-space theory models problem solving as a navigation through a structured space of states, operators, goals, and constraints. Systems Engineering (SE) employs analogous constructs (functional analysis, operational analysis, scenarios, trade studies), yet still lacks a rigorous systems-theoretic representation of the problem space itself. In current practice, reasoning often proceeds directly from stakeholder goals to prescriptive artifacts. This makes foundational assumptions about the operational environment, admissible interactions, and contextual conditions implicit or prematurely embedded in architectures or requirements. This paper addresses that gap by formalizing the problem space as an explicit semantic world model containing theoretical constructs that are defined prior to requirements and solution commitments. These constructs along with the developed axioms, theorems and corollary establish a rigorous criterion for unambiguous boundary semantics, context-dependent interaction traceability to successful stakeholder goal satisfaction, and sufficiency of problem-space specification over which disciplined reasoning can occur independent of solution design. It offers a clear distinction between what is true of the problem domain and what is chosen as a solution. The paper concludes by discussing the significance of the theory on practitioners and provides a dialogue-based hypothetical case study between a stakeholder and an engineer, demonstrating how the theory guides problem framing before designing any prescriptive artifacts.
SONG Shilong1, 2, LIAO Lei1, 2, LEI Hao2, MA Lan3, ZHANG Yongde2, , ZOU Hao2,
Nowadays, fast breeder reactor (FBR) is one of the preferred reactor types for Generation Ⅳ advanced nuclear energy systems in the world. FBRs can improve the utilization rate of uranium resources, make the long-lived spent fuel generation much lower, and achieve the minimization of radioactive waste. The characteristics of high burnup, high irradiation, and high plutonium content of fast reactor spent fuel make it difficult for the traditional aqueous reprocessing process to meet the separation needs. Compared with the traditional liquid separation technology, dry technology has potential advantages and dry reprocessing is mainly under high temperature argon environment, for the treatment of radioactive gases in the spent fuel reprocessing process, as the 129I containing exhaust gas has attracted much attention due to its long half-life, high content and high toxicity. In this paper, Bi(NO3)3·5H2O was used as the source of bismuth, L-cysteine as the source of sulfur, and ethylene glycol as the solvent, two-step hydrothermal method was used to prepare bismuth sulfide modified zeolite composites (Bi2S3-MOR). The static adsorption experiments were carried out in a reactor with a valve, where the composites were first placed in a polytetrafluoroethylene liner together with iodine (methyl iodide), and the experiments were kept in an argon environment by closing the valve after 20 min of argon gas was passed through the valve. The physical phase of the composites was analyzed by XRD, the specific surface area and pore size by BET, the structure of functional groups by FT-IR, the morphology of the materials before and after modification and the distribution of the elements by SEM and EDS, the loading after modification by ICP-OES, and the content of C and H in the composites by elemental analyzer, and the valence change of the composites before and after the adsorption as well as the strength of the binding energy were analyzed by XPS, the thermal stability of the composites was analyzed by TGA. The experimental results show that the static adsorption capacity of bismuth sulfide modified zeolite for monosubstituted iodine is up to 180 mg/g at 130 ℃ under argon environment, and the trapping forms are both chemisorbed BiI3 and physisorbed I2, while the static adsorption capacity for CH3I is 50 mg/g at 50 ℃ under argon environment, and only the chemical adsorption in the form of BiI3 exists. The research results can provide new ideas and options for the purification and treatment of gaseous radioactive iodine in the dry reprocessing process.
The urgent requirement for sustainable and dependable energy sources has stimulated an increased fascination with precisely forecasting nuclear energy generation. This work utilizes sophisticated regression modeling approaches, namely XGBoost, to predict nuclear energy generation by leveraging economic indices such as Gross Domestic Product (GDP). Each model's prediction accuracy has been evaluated by examining historical data on nuclear energy output and GDP from various locations. Here, measures such as mean squared error (MSE) and coefficient of determination (R2) to analyze their effectiveness have been used. The results of this study demonstrate that the XGBoost model outperforms standard regression approaches, showing greater R2 values and lower MSE scores. Furthermore, the consequences of these discoveries for the development of energy policy offer possible directions for future study in energy forecasting. This study provides useful insights for energy planners and policymakers, enabling a more profound comprehension of the complex relationship between economic indicators and nuclear energy generation.
A. Ramachandra Murthy, Divyansh Kale, M. Saravanan
et al.
This paper presents the details of Artificial Neural Network (ANN) based models to predict crack depth and remaining life of circumferentially part-through cracked piping components used in the nuclear industry. Crack growth data from experimental studies on (i) straight pipes made up of SA 312 Type 304 LN stainless steel having part-through circumferential notch under combined bending and torsion and (ii) dissimilar metal pipe weld joints having circumferential through-wall crack in the weld were used. The dissimilar metal pipe weld joint is made up of SA312 Type 304 LN austenitic stainless steel and SA508 Gr. 3 Cl. 1 low alloy carbon steel and joined by Nickel-rich Inconel alloy weld. About 75 % of the mixed experimental data has been used for development of model and the remaining data for validation. For the development of ANN model, (i) back propagation technique (ii) sigmoidal transfer functions and (iii) Levenberg-Marquardt algorithm are used. The maximum percentage difference observed between the predicted and the experimental results for crack depth and remaining life was 19.59 % and 15.78 % respectively. The efficiency of the developed model was verified using several statistical parameters. The developed models are useful for the structural integrity assessment of piping components under different loading scenarios.
Robert A. Mostoghiu Paun, Darren Croton, Chris Power
et al.
Traditional N-body methods introduce localised perturbations in the gravitational forces governing their evolution. These perturbations lead to an artificial fragmentation in the filamentary network of the Large Scale Structure, often referred to as "beads-on-a-string." This issue is particularly apparent in cosmologies with a suppression of the matter power spectrum at small spatial scales, such as warm dark matter models, where the perturbations induced by the N-body discretisation dominate the cosmological power at the suppressed scales. Initial conditions based on third-order Lagrangian perturbation theory, which allow for a late-starting redshift, have been shown to minimise numerical errors contributing to such artefacts. In this work, we investigate whether the additional use of a spatially adaptive softening for dark matter particles, based on the gravitational tidal field, can reduce the severity of artificial fragmentation. Tidal adaptive softening significantly improves force accuracy in idealised filamentary collapse simulations over a fixed softening approach. However, it does not substantially reduce spurious haloes in cosmological simulations when paired with such optimised initial conditions. Nevertheless, tidal adaptive softening induces a shift in halo formation times in warm dark matter simulations compared to a fixed softening counterpart, an effect not seen in cold dark matter simulations. Furthermore, initialising the initial conditions at an earlier redshift generally results in z=0 haloes forming from Lagrangian volumes with lower average sphericity. This sphericity difference could impact post-processing algorithms identifying spurious objects based on Lagrangian volume morphology. We propose potential strategies for reducing spurious haloes without abandoning current N-body methods.
For Safety Assisted Engineering works, real-time simulators have emerged as a mandatory tool among all the key actors involved in the nuclear industry (utilities, designers and safety authorities). EDF, Electricité de France, as the leading worldwide nuclear power plant operator, has a crucial need for efficient and updated simulation tools for training, operating and safety analysis support.This paper will present the work performed at EDF/DT to develop a new generation of engineering simulator to fulfil these tasks. The project is called SiRENE, which is the acronym of Re-hosted Engineering Simulator in French. The project has been economically challenging. Therefore, to benefit from existing tools and experience, the SiRENE project combines:- A part of the process issued from the operating fleet training full-scope simulator.- An improvement of the simulator prediction reliability with the integration of High-Fidelity models, used in Safety Analysis. These High-Fidelity models address Nuclear Steam Supply System code, with CATHARE thermal-hydraulics system code and neutronics, with COCCINELLE code.- And taking advantage of the last generation and improvements of instructor station.The intensive and challenging uses of the new SiRENE engineering simulator are also discussed. The SiRENE simulator has to address different topics such as verification and validation of operating procedures, identification of safety paths, tests of I&C developments or modifications, tests on hydraulics system components (pump, valve etc.), support studies for Probabilistic Safety Analysis (PSA). etc. It also emerges that SiRENE simulator is a valuable tool for self-training of the newcomers in EDF nuclear engineering centers.As a modifiable tool and thanks to a skillful team managing the SiRENE project, specific and adapted modifications can be taken into account very quickly, in order to provide the best answers for our users' specific issues.Finally, the SiRENE simulator, and the associated configurations, has been distributed among the different engineering centers at EDF (DT in Lyon, DIPDE in Marseille and CNEPE in Tours). This distribution highlights a strong synergy and complementarity of the different engineering institutes at EDF, working together for a safer and a more profitable operating fleet.
WEI Ke1, 2, PI Lixin1, , WANG Hui1, LIU Chao1, ZHANG Peng1
Ferritic/martensitic stainless steel has a wide range of applications in reactor engineering. During the service phase, reactor materials are required to have good resistance to high temperatures, radiation, and creep. During the retirement phase, it is required that the materials must be kept at a lower temperature in the spent fuel pool and prevent the diffusion of radioactive products. This paper focuses on the alternative material of ferritic/martensitic stainless steel for a specially designed reactor cladding. This paper used electrochemical experimental methods to establish an electrochemical corrosion model to study the corrosion behavior of the material in low-temperature water environments, providing reference for environmental condition control of the material during retirement. The sample was processed by wire cutting method, cleaned with acetone and deionized water, dried, and then connected to the wire by welding. The sample was encapsulated with resin and curing agent. The open circuit potential, polarization curve, and electrochemical impedance spectrum of the sample were measured in aqueous solutions with different chloride ion concentrations and temperatures, and the equivalent circuit fitting of the material was carried out. The experimental results show that stainless steel can generate a protective passivation film in pure water, and the properties of the passivation film change with changes in external conditions. In the early stage of corrosion, a highly corrosive environment has a certain promoting effect on the formation of passivation film. The increase in chloride ion concentration lowers the breakdown potential, impedance, and stability of the passivation film, reduces the solution resistance, and leads to a decrease in the corrosion resistance of the material. The increase in temperature reduces the stability of the passivation film. When the temperature is between 30, 40, 50 ℃, the surface properties of the material are relatively stable, and the tendency for severe corrosion is relatively small. The critical pitting temperature of the materials used in the experiment is between 60, 70 ℃. When the temperature exceeds 60 ℃, the radius of the surface impedance spectrum arc of the material significantly decreases. The activity of electrochemical corrosion is mainly attributed to the decrease in resistance of the passivation film, and this change becomes more pronounced when the temperature exceeds the critical pitting temperature. Therefore, when the chloride ion concentration is less than 10 ppm and the temperature is less than 60 ℃, the surface passivation film stability of the sample stainless steel is good, and the material has strong corrosion resistance. This condition can be used as a reference condition for the water quality control of the spent fuel pool.
The multi-dimensional thermal-hydraulic phenomena in the downcomer of advanced pressurized water reactor with direct vessel injection system are the key points for the safety analysis during a loss of coolant accident. In order to improve the accuracy of LOCUST code for the predictions of thermal-hydraulic phenomena in downcomer region, some newly correlations have been implemented into LOCUST code. The wall friction model of LOCUST code was modified based on the correlations which developed by Yang. The interfacial friction models in LOCUST code have been modified as Hibiki-Ishii correlations. In addition, in order to simulate the upward flow of recirculation flow in downcomer region, the Kinoshita-Hibiki correlations have been also implemented into LOCUST code for better simulating the recirculation flow in downcomer region. The modified code was validated with experimental data of DOBO facility. Five tests of DOBO facility have been calculated by LOCUST, and the calculated axial void fraction distributions have been compared with the measurements. The results show that the modified LOCUST with new correlations of distribution parameter and drift velocity shows better accuracy than the original code. The deviations of the modified LOCUST code are less than the original code and are almost within ±20 %.
LinkedIn is the largest professional network in the world. As such, it can serve to build bridges between practitioners, whose daily work is software engineering (SE), and researchers, who work to advance the field of software engineering. We know that such a metaphorical bridge exists: SE research findings are sometimes shared on LinkedIn and commented on by software practitioners. Yet, we do not know what state the bridge is in. Therefore, we quantitatively and qualitatively investigate how SE practitioners and researchers approach each other via public LinkedIn discussions and what both sides can contribute to effective science communication. We found that a considerable proportion of LinkedIn posts on SE research are written by people who are not the paper authors (39%). Further, 71% of all comments in our dataset are from people in the industry, but only every second post receives at least one comment at all. Based on our findings, we formulate concrete advice for researchers and practitioners to make sharing new research findings on LinkedIn more fruitful.
GUARDYAN is a GPU-based dynamic Monte Carlo code developed at the Budapest University of Technology and Economics, Hungary. Dynamic Monte Carlo computes the neutron population evolution by calculating the direct time dependence of the neutron histories in multiplying systems. Some well-established Monte Carlo codes have DMC versions with coupling to Thermal-Hydraulic solvers. GUARDYAN has the computational advantage of applying GPUs, thus calculation burden can be carried by commonly available hardware, and is capable of handling power plant size systems for kinetics problems. GUARDYAN has been recently coupled to the subchannel thermal-hydraulics code SUBCHANFLOW in order to carry out dynamic calculations with TH feedback. This paper describes some convergence studies regarding reaching the initial equilibrium state. A literature-suggested set of TH input settings and high sample numbers resulted in very low statistical errors of the power estimates and stable global measures (L2) of power release, fuel, and coolant temperatures for both static and dynamic convergence. Dynamic mode low-sample simulations provided surprisingly stable global L2 measures, correct fuel temperatures, and power release, while coolant temperatures were off, without any indication of the incorrectness of the result. Static convergence showed an alternating, fluctuating L2 behavior that did not affect the final stable state.
2D/1D coupling method is an important neutron transport calculation method due to its high accuracy and relatively low computation cost. However, 2D/1D coupling method may diverge especially in small axial mesh size. To analyze the convergence behavior of 2D/1D coupling method, a Fourier analysis for k-eigenvalue neutron transport problems is implemented. The analysis results present the divergence problem of 2D/1D coupling method in small axial mesh size. Several common attempts are made to solve the divergence problem, which are to increase the number of inner iterations of the 2D or 1D calculation, and two times 1D calculations per outer iteration. However, these attempts only could improve the convergence rate but cannot deal with the divergence problem of 2D/1D coupling method thoroughly. Moreover, the choice of axial solvers, such as DGFEM SN and traditional SN, and its effect on the convergence behavior are also discussed. The results show that the choice of axial solver is a key point for the convergence of 2D/1D method. The DGFEM SN based 2D/1D method could converge within a wide range of optical thickness region, which is superior to that of traditional SN method.
Today, many systems use artificial intelligence (AI) to solve complex problems. While this often increases system effectiveness, developing a production-ready AI-based system is a difficult task. Thus, solid AI engineering practices are required to ensure the quality of the resulting system and to improve the development process. While several practices have already been proposed for the development of AI-based systems, detailed practical experiences of applying these practices are rare. In this paper, we aim to address this gap by collecting such experiences during a case study, namely the development of an autonomous stock trading system that uses machine learning functionality to invest in stocks. We selected 10 AI engineering practices from the literature and systematically applied them during development, with the goal to collect evidence about their applicability and effectiveness. Using structured field notes, we documented our experiences. Furthermore, we also used field notes to document challenges that occurred during the development, and the solutions we applied to overcome them. Afterwards, we analyzed the collected field notes, and evaluated how each practice improved the development. Lastly, we compared our evidence with existing literature. Most applied practices improved our system, albeit to varying extent, and we were able to overcome all major challenges. The qualitative results provide detailed accounts about 10 AI engineering practices, as well as challenges and solutions associated with such a project. Our experiences therefore enrich the emerging body of evidence in this field, which may be especially helpful for practitioner teams new to AI engineering.
This paper describes how motivational models can be used to cross check agile requirements artifacts to improve consistency and completeness of software requirements. Motivational models provide a high level understanding of the purposes of a software system. They complement personas and user stories which focus more on user needs rather than on system features. We present an exploratory case study sought to understand how software engineering students could use motivational models to create better requirements artifacts so they are understandable to non-technical users, easily understood by developers, and are consistent with each other. Nine consistency principles were created as an outcome of our study and are now successfully adopted by software engineering students at the University of Melbourne to ensure consistency between motivational models, personas, and user stories in requirements engineering.
This proceeding consists of the peer-reviewed papers from the 3rd International Conference on Sustainable Energy Solutions for a Better Tomorrow (SESBT 2022), which was organized by the School of Mechanical Engineering of Vellore Institute of Technology, Chennai in collaboration with Energy and Sustainability Research Institute of Groningen (ESRIG), University of Groningen, Netherlands on July 23rd and 24th, 2022. For more details about SESBT 2022, please visit www.vitsesbt.com. However, due to the COVID 19 pandemic the conference was held Online. The main objective of SESBT 2022 is to provide a platform for researchers and technocrats from both academic institutions and industries to meet and share cutting-edge developments in the areas of sustainable energy and associated disciplines. This conference also provided an opportunity to exchange research evidence and innovative ideas and also the issues related to sustainable energy. This proceeding will include presentations on the latest research areas such as Carbon Neutrality, Electric & Hybrid Vehicles, Green and Energy Efficient Buildings, Energy Storage, Computational Models for Energy Systems, Advanced Cryo techniques, AI in Energy Systems, Thermal System Optimization and Renewable Energy. The conference was inaugurated on July 23, 2022 by the renowned scientist, Shri.S.Raghupathy, Director – Reactor Design and Technology Group, EIG, Indira Gandhi Centre for Atomic Research, Kalpakkam, India in the presence of Dr.M.Muthuraman, Additional General Manager, Environment Management Group, NTPC Sipat. International Chair, Prof.P.V.Aravind, Full Professor and Chair of Energy Conversion, University of Groningen, Netherlands, Prof.P.C.Sabumon, Dean Academics Research, VIT Chennai and Conference Chair, Dr.K.Annamalai, Dean and Professor, School of Mechanical Engineering, VIT Chennai also felicitated the ceremony. This conference had gathered an excellent group of keynote speakers from across the globe on 12 different topics such as Nuclear Power to Combat Climate Change, On the Design of Latent Thermal Energy Storage for Air conditioning and Space Heating, Thermodynamic Performance Assessment of Solar Chimney Power Plants: Design, Climate and Operational Aspects, Renewable Energy for Sustainable Automotive Engineering, Optimization of a Polymer Electrolyte Membrane Electrolyser – Every Little Helps, Desalination Process based on Renewable Energy, Liquid Cooled Electric Motors for High Performance, Sustainable Composite Materials for Future, Green Hydrogen: Seizing Today’s Opportunities, Chromogenic Materials for Energy Saving, Influence of Reflectors on Photovoltaic Module Efficiency for Sewage Treatment and Wayanad Carbon Neutrality Program. The keynote speakers are Shri.S.Raghupathy from IGCAR, Dr.Simone Mancin from University of Padua, Italy, Dr.Erdem Cuce from Recep Tayyip Erdogan University Rize, Turkey, Prof. M.M.Noor Universiti Malaysia Pahang, Dr.Mamdud Hossain from Robert Gordon University, UK, Prof.K.Srithar from Thiagarajar College of Engineering, Madurai, India, Prof.Satish Kumar from Georgia Tech, USA, Dr.Devendran Thirunavukarasu from ST Advanced Composites Chennai, India, Prof.S.Vasudevan from CECRI, Dr.Alessandro from Politechnico di bari, Italy, Prof.Mohd Zulkifly Abdullah from University Sains Malaysia, and Dr.P.V.Aravind from University of Groningen. In addition, a special talk on Sustainability with nuclear power – small modular reactor by Mr.Aniket Joshi from The Open University, UK was arranged. This year, SESBT 2022 received more than 200 technical articles from across the globe. A total of 154 research articles were shortlisted and 140 research articles were presented. Based on the scope of the IOP Conference Series: Earth and Environmental Science (EES) and submission of undertaking by authors, only 35 papers were uploaded in Morressier platform. Upon completion of the single blind peer review process, 16 papers were accepted for publication in IOP Conference Series: Earth and Environmental Science (EES). The evaluation of all the papers was performed based on the reports from anonymous reviewers. List of SESBT 2022 – Committee Members, Advisory Committee, Conference Chairs, International Expert Committee, Executive Committee, Technical Committee, Organizing Committee, Editors are available in the pdf.
Two groups of oxide dispersion–strengthened reduced-activation ferritic/martensitic steels (A and B) were prepared by adding Y, Ti, and Zr into steels through vacuum induction melting to investigate the inclusions, microstructures, mechanical properties of the alloys. Results showed that particles with Y, Ti, and Zr easily formed. Massive, Zr-rich inclusions were found in B steel. Density of micron inclusions in A steel was 1.42 × 1014 m−3, and density of nanoparticles was 3.61 × 1016 m−3. More and finer MX carbides were found in steel tempered at 650 °C, and yield strengths (YS) of A and B steel were 714±2 and 664±3.5 MPa. Thermomechanical processing (TMP) retained many dislocations, which improved the mechanical properties. YSs of A and B treated by TMP were 725±3 and 683±4 MPa. The existence of massive Zr-rich inclusions in B steels interrupted the continuity of the matrix and produced microcracks (fracture), which caused a reduction in mechanical properties. The presence of fine prior austenite grain size and inclusions was attributed to the low DBTTs of the A steels; DBTTs of A650 and A700 alloy were −79 and −65 °C. Tempering temperature reduction and TMP are simple, readily useable methods that can lead to a superior balance of strength and impact toughness in industry applications.
Purpose: To understand the influence of radon on human health in underground microenvironment of iron mine, and find the sensitive detection index of the influence of radon cumulative exposure on human health. Methods: According to National Work Manual of Occupational Radiation disease Surveillance (Survey of Miners with High radon Exposure) and expert consensus on low-dose spiral CT lung cancer screening. Selected 51 underground workers in an iron mine as the observation objects, using chromosome aberration of peripheral blood lymphocytes, micronucleus of lymphocytes, tumor markers of serum and low-dose CT screening of lung cancer as observation indexes. Results: 6 cases with elevated lymphocyte count (11.8%), NSE (neuron specific enolase) elevation detected 20 (39.2%), abnormal detection of SCC (Squamous cell carcinoma associated antigen) 13 (22.5%), Cyfra21-1 (cytokeratin 19 fragment) was detected 3 (5.9%). Chromosomal abnormalities and micronucleus abnormalities were detected 1 (2.0%). Thyroid nodules were detected 10 (19.6%). Low-dose chest CT detection plaques and funicular shadow 21 (41.2%), nodules 16 (31.4%), bulla 9 (17.6%) frosted (2.0%). Conclusion: In this study, based on the survey and monitoring data of miners in a deep mine, there is a health risk with radon exposure in the occupational health of iron ore workers, in particular, radon exposure causes lung cancer risk, which is a public health problem to be solved.
Medical physics. Medical radiology. Nuclear medicine, Nuclear engineering. Atomic power
A numerical particle simulation code package to estimate the irradiation distribution of an electron beam machine is presented. Particle-to-particle interactions are calculated using particle-in-cell method, while the equation of motion is solved using Boris algorithm. The amplitude of oscillating magnetic field distribution from the scanning horn is obtained using CST magnetic field solver. The code was run using Intel’s i7-10700 processor without multithreading. For cases where particle-to-particle interactions are negligible, the simulation requires about 10 000 seconds to finish. The results show that different shapes of signals will result in different irradiation distributions. For a relatively low magnetic oscillation frequency, it is shown that a triangular signal will result in a more evenly distributed irradiation compared to a sinusoidal signal.
The digital beam position monitor processer (DBPM) is one of the important beam diagnosis equipments in particle accelerator and it will be massproduced during the construction of Upgrade of Beijing Electron Positron Collider (BEPCⅡ) and high energy photon source (HEPS), which brings great challenges to the testing work. The analog to digital converter (ADC) module is an essential component of DBPM and its conversion accuracy determines the resolution of the beam position measurement. Therefore, in order to ensure that these two projects meet the design targets, it is necessary to test the ADC performance. Its main observation object includes the phaselocked loop, sampling clock jitter, signaltonoise ratio (SNR), etc. To meet the batch test requirements of the selfdeveloped DBPM ADC, a method of testing the sampling performance based on the histogram was proposed. The histogram’s test principle is that the shape of the histogram can detect whether the sampling clock is phaselocked to the input signal, the boundary value of the histogram reflects the amplitude of the input signal to judge if the ADC is saturated, and the average and standard deviation of the data peak on the histogram can be used to calculate the clock jitter that conforms to the normal distribution. In this paper, the mathematical relation between the statistics of each data peak, clock jitter, and SNR was simulated by MATLAB in the situation of phaselocking. The separation algorithm was designed to obtain the data corresponding to each peak of the histogram and compute the clock jitter and SNR. An integrated test platform was built and experiments were carried out to verify the testing effect of the histogram method. The experimental results show that when the amount of sampling data is appropriate, the histogram method can complete the test quickly and accurately, and the measurement result is close to that of the highperformance phase noise analyzer. The clock jitter measurement error is less than 200 fs, the SNR measurement error is less than 2 dB, and the entire test duration is less than 1 min, which fulfills large volume testing demands. Compared with the manual instrument measure method, the histogram approach is simpler and lower cost to test with the same order of magnitude accuracy and has been implemented by programming to reduce labor intensity. The test program has been implemented in the automatic test platform and used to batch detection of DBPM products successfully.