Karlsruhe Institute Of Technology Research Articles

AN OVERVIEW AND ANALYSIS OF SILENT SOUND TECHNOLOGY

‌Nowadays whenever we are in a crowd or there was a to much background noise around us then it is very difficult to communicate or interact over the phone, but now we have an awesome solution on this problem that is ' silent sound technology ' it is a gift for those who lost their voice but wish to speak over the phone. this technology is produced by the Karlsruhe institute of technology, Germany and it will be available soon in the market. Silent sound technology is also known as ultrasonic sound or ultrasonic communication enables the transmission of data through inaudible sound waves. in this technology it detects every lip movement and convert it into the sound signal neglecting all background noise. without using real audio it is a visual interpretation of lip, mouth and face. So basically it reads our lip. This technology is available in English, German and French language, but not in language like Chinese because different tones hold different meanings in Chinese language. it use to allow silent calls and we can share our personal information like PIN , password or secret information to trusted one without knowing any other. it is also use in the Military for the secret missions. According to the researchers the technology have 99% efficiency only 1% possibility that it was produce a incorrect voice and upcoming 6-7 years the normal peoples are also use this technology because it launching very soon. Keywords : silent sound technology, electromyography, image processing.

Curvature Scale Space LiDAR Odometry And Mapping (LOAM)

The LiDAR Odometry and Mapping (LOAM) algorithm ranks in second place in the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI), Visual Odometry/SLAM Evaluations. It utilizes a feature extraction algorithm based on the evaluation of the curvature of points under test, to produce estimated smooth and non-smooth regions within typically laser based Point Cloud Data (PCD). This feature extractor (FE) however, does not take into account PCD spatial or detection uncertainty, which can result in the divergence of the LOAM algorithm. Therefore, this article proposes the use of the Curvature Scale Space (CSS) algorithm as a replacement for LOAM’s current feature extractor. It justifies the substitution, based on the CSS algorithm’s similar computational complexity but improved feature detection repeatability. LOAM’s current feature extractor and the proposed CSS feature extractor are tested and compared with simulated and real data, including the KITTI odometry-laser data set. Additionally, a recent deep learning based LiDAR Odometry (LO) algorithm, the Convolutional Auto-Encoder (CAE)-LO algorithm, will also be compared, using this data set, in terms of its computational speed and performance. Performance comparisons are made based on the Absolute Trajectory Error (ATE) and Cardinalized Optimal Linear Assignment (COLA) metrics. Based on these metrics, the comparisons show significant improvements of the LOAM algorithm with the CSS feature extractor compared with the benchmark versions.

Using conditional Invertible Neural Networks to perform mid‐term peak load forecasting

AbstractMeasures for balancing the electrical grid, such as peak shaving, require accurate peak forecasts for lower aggregation levels of electrical loads. Thus, the Big Data Energy Analytics Laboratory (BigDEAL) challenge—organised by the BigDEAL—focused on forecasting three different daily peak characteristics in low aggregated load time series. In particular, participants of the challenge were asked to provide long‐term forecasts with horizons of up to 1 year in the qualification. The authors present the approach of the KIT‐IAI team from the Institute for Automation and Applied Informatics at the Karlsruhe Institute of Technology. The approach to the challenge is based on a hybrid generative model. In particular, the authors use a conditional Invertible Neural Network (cINN). The cINN gets the forecast of a sliding mean as representative of the trend, different weather features, and calendar information as conditioning input. By this, the proposed hybrid method achieved second place overall and won two out of three tracks of the BigDEAL challenge.

An Overview of Mechanisms of the Degradation of Promising ATF Cladding Materials During Oxidation at High Temperatures

AbstractAccident tolerant fuel (ATF) cladding is a new type of nuclear fuel cladding designed to improve the safety and performance of nuclear reactors. In this paper, the kinetics and degradation mechanisms during high-temperature oxidation in steam of the three most promising ATF cladding materials, i.e., chromium-coated zirconium alloys, FeCrAl alloys, and silicon carbide-based composites, are described. Each system has its own degradation mechanisms leading to different maximum survival temperatures. After providing general information and data to understand the oxidation and degradation processes, illustrative examples obtained at the Karlsruhe Institute of Technology are given for each type of cladding. The maximum temperatures at which the barrier effect of the cladding can be maintained for a reasonable period of time during nuclear accident scenarios are 1200–1300 °C for Cr-coated Zr alloys, 1400 °C for FeCrAl alloys, and 1700 °C for SiC-based composite claddings.

Bending Behavior of Hybrid Timber-Steel Beams.

Driven by climate change and the need for a more sustainable construction sector, policy is increasingly demanding and promoting timber hybrid construction methods. In the German state of Baden-Württemberg, every new public building has to be of timber or timber hybrid construction (Holzbauoffensive BW). The objective of multi-story buildings with large floor spans can only be achieved in a resource-efficient way by hybrid constructions combining timber and steel components. A research project recently completed at the Karlsruhe Institute of Technology was aimed at the development and systematic investigation of hybrid bending beams in which an advantageous combination of the materials steel and timber is used. For this purpose, steel profiles are integrated into timber cross-sections in a shear-resistant manner by adhesive bonding. As part of the experimental, numerical and analytical investigations, different cross-sections of steel and timber, as well as different construction materials, were considered (GL24h, LVL48p, LVL80p, S355 and S420). The results of large-scale four-point bending tests illustrate the potential of this new hybrid construction method. Depending on the geometry and material combinations tested, the bending stiffness could be increased by up to 250%, and the load-carrying capacity by up to 120%, compared to a glulam beam with identical dimensions.

Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases

Existing testing methods for Automatic Emergency Braking (AEB) systems mostly rely on standard-based qualitative analysis of specific scenarios, with a focus on whether collisions occur. To explore scenarios beyond the standard conduct, a comprehensive testing model construction and analysis, and provide a more quantitative evaluation of AEB performance, this study extracted three typical hazardous driving scenarios from the KITTI (The Automated Driving dataset was created by the Karlsruhe Institute of Technology in Germany and the Toyota Institute of Technology in the United States) naturalistic driving dataset using kinematic data. A DME (Data Missing Estimation) scene construction method was proposed, and these scenarios were simulated and reconstructed in PRESCAN (PRESCAN is an automotive simulation software owned by Siemens, Munich, Germany). A C-AEB (Curve-Automatic Emergency Braking) testing model was developed and tested based on simulations. Finally, a BCEM (Boundary collision evaluation model) was proposed to quantitatively evaluate AEB performance. The focus of the analysis was on the identified cornering scenario A (severely failed AEB scenario). A C-AEB testing model was constructed based on the DME scene construction method for this cornering AEB failure scenario, and it was evaluated using the BCEM. The study found that the average performance degradation rate (performance degradation rate refers to the ratio of AEB performance in the current scenario compared to the standard straightaway test) of the AEB system in this cornering scenario reached 75.44%, with a maximum performance degradation rate of 89.47%. It was also discovered that the severe failure of AEB in this cornering scenario was mainly caused by sensor system perception defects and limitations of traditional AEB algorithms. This fully demonstrates the effectiveness of our testing and evaluation methodology.

An Attention-Based Odometry Framework for Multisensory Unmanned Ground Vehicles (UGVs)

Recently, deep learning methods and multisensory fusion have been applied to address odometry challenges in unmanned ground vehicles (UGVs). In this paper, we propose an end-to-end visual-lidar-inertial odometry framework to enhance the accuracy of pose estimation. Grayscale images, 3D point clouds, and inertial data are used as inputs to overcome the limitations of a single sensor. Convolutional neural network (CNN) and recurrent neural network (RNN) are employed as encoders for different sensor modalities. In contrast to previous multisensory odometry methods, our framework introduces a novel attention-based fusion module that remaps feature vectors to adapt to various scenes. Evaluations on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago (KITTI) odometry benchmark demonstrate the effectiveness of our framework.

Uncertainty and Sensitivity Evaluation of the QUENCH-02 Experiment Simulation Using the ASYST Code

Abstract Uncertainty and sensitivity methods are increasingly used in safety analyzes of nuclear power plants to address the unreliability of input data, numerical models, and, in general, the lack of knowledge regarding certain physical phenomena, in determining safety margins and acceptance criteria. The ASYST code, developed as part of an international nuclear technology ASYST Development and Training Program (ADTP) managed by Innovative Systems Software (ISS), is used to perform an uncertainty analysis of the QUENCH-02 experiment conducted at the Karlsruhe Institute of Technology. The code uses a probabilistic methodology based on the propagation of input uncertainties. The QUENCH facility contains electrically heated PWR fuel rod simulators and the aim of the experiment is to examine hydrogen generation and the behavior of the fuel rod cladding during core reflood. For selected input parameters, such as steam/water flow, electrical power, and other relevant boundary conditions, it is necessary to define their probability density functions. Input databases are then prepared for individual calculations based on the selected confidence level and confidence interval. The number of performed calculations is 60, large enough to ensure at least 95% coverage of expected output results and uncertainty limits. The results of the calculations are compared with the experimental measurements. The Pearson correlation coefficient is used to obtain correlation between the input uncertain parameters and the output data. Sensitivity analyses cover the influence of variations in the heater's electrical power and the steam flow rate on the hydrogen production and the maximum cladding temperature.

The SPIZWURZ project – Experimental investigations and modeling of the behavior of hydrogen in zirconium alloys under long-term dry storage conditions

In order to investigate the occurring processes during long-term dry storage of spent fuel assemblies, a joined project called SPIZWURZ, between the Karlsruhe Institute of Technology and the Gesellschaft für Anlagen-und Reaktorsicherheit (GRS), was started. Aim of the SPIZWURZ project is the determination and quantification of the influence of texture and elastic strain on diffusion and solubility of hydrogen in three different zirconium alloys used in western Europe during a long-term cooling transient (1 K/d) starting at 400 °C. The strain in the cladding of an irradiated spent fuel rod shall be measured. Models predicting the formation of radial oriented hydrides will be validated, improved, and implemented in the GRS fuel rod performance code TESPA-ROD. This paper describes the SPIZWURZ project and already obtained first results.

KIT reactor safety research for LWRs: Research lines, numerical tools, and prospects

This paper describes the main research lines of the Karlsruhe Institute of Technology (KIT) relevant to Light Water Reactors (LWR) that permit both the safety evaluation of different reactor designs and the prediction of the radiological source term including its impact in the case of hypothetical severe accidents. The numerical tools for core analysis, nuclear power plant analysis of design basis and severe accidents, and the estimation of the radioactive dispersions of fission products after a core meltdown accident are described and selected results are discussed. The analytical investigations at KIT are complemented by experimental investigations at two facilities, namely the COSMOS-H/-L and the QUENCH facilities devoted to safety-relevant Thermal-Hydraulic (TH) phenomena and in-vessel severe accident early-phase for different kinds of fuel rods including Accident Tolerant Fuel (ATF). These data are crucial for the validation of the numerical tools used for safety demonstration. The paper is complemented by a brief description of the in-house tools under development for improved core/plant analysis based on the multi-physics/-scale coupling methodologies, where the in-house tools are combined with external system TH, Monte Carlo, and thermo-mechanic code to increase the prediction accuracy of the core/plant behaviour under stationary and accidental conditions. Selected results are presented and discussed. It can be stated that the long-lasting safety research activities at KIT devoted to LWR led to the development of a computation route combining external with in-house codes that is very much appropriate for safety evaluations and risk assessment; it includes unique multi-physics/-scale coupled tools for improved core and plant analysis of different reactor designs, e.g. PWR, VVER, BWR, SMR, and research reactors.

Nuclear decommissioning: project management and leadership

Abstract. Management and leadership for safety relate to managerial competencies necessary to develop, promote and sustain a safety culture and to set goals, lead others and manage knowledge and projects to enhance safety performance. The development of these competencies is needed to enrich and complement the predominant technical background and skills of engineers and/or managers involved in the nuclear sector and particularly in decommissioning and dismantling (D&D) projects. The recent recognition of the importance of managing for safety led the International Atomic Energy Agency (IAEA) to develop formal safety requirements that are now implemented by its member states. This includes the need to develop training and education for beginning- and mid-career managers with nuclear safety responsibilities and, considering the time frame of D&D projects, for future generations of managers. Training and education challenges are acute in all Instrument for Nuclear Safety Cooperation (INSC) and European countries, where managers need to develop knowledge and comprehensive safety-related competencies to run the D&D projects of nuclear facilities in a context where the generational change of managers in the nuclear field is happening fast. In 2016/2017 the IAEA and the European Commission (EC) developed a cooperative framework to jointly address a similar challenge related to operation and regulatory oversight of nuclear installations. The development of these projects was possible by funding from the European Union (EU) through its INSC instrument. The first project, led by the IAEA in 2017, was the development of a pilot school for safety leadership at the University Côte d'Azur (UCA), France. Encouraged by this success, the agency has since then developed the syllabus into a 2-week programme, still based on experiential learning, which is offered to IAEA member states who wish to organise sessions for their managers (regulatory bodies or industry). The second project, named ELSE, was operated by UCA and aimed to develop training to help managers acquire leadership for safety capabilities, which are key professional requirements in complex, high-risk and highly regulated sectors such as the nuclear sector. The originality of the ELSE project stemmed from its science-based approach, integrating the most recent findings of management and other social sciences. The dedicated ELSE training programme is composed of a massive online open course (MOOC), a 10 d of face-to-face training and an individually tutored project. Based on the success of these experiences, the EU decided to prolong these actions in the field of nuclear D&D, leading to the start-up, in 2023, of the Decommissioning Management and Leadership for Safety Education (DMaLSE) project. This project has also been entrusted to UCA, in partnership with SKEMA Business School, the Karlsruhe Institute of Technology (KIT) and Jacques Repussard Conseil. DMaLSE has two main objectives, namely to develop a science-based training programme for future D&D project managers and to extend the impact of the project through bachelor-degree-level on-site training for operators involved in D&D projects.

Experimental investigation of uranium release from spent nuclear fuels under conditions expected in a deep geological repository

Abstract. Direct disposal of spent nuclear fuel (SNF) in a deep geological repository is planned for the long-term management of the highly radioactive waste discharged from the light water reactors (LWRs) of nuclear power plants in Germany. The aim is to safely isolate the radionuclide inventory from the biosphere, ad infinitum, making use of a multi-barrier system consisting of technical, geotechnical and geological barriers interposed between the emplaced waste and the environment. Still, reversibility measures including retrievability of the waste products are considered in this concept. Internationally, in safety assessments for deep underground repositories (DGRs), the access of groundwater, followed by failure of canisters and finally loss of the SNF's cladding integrity is considered in the long term. Hence, the evaluation of the performance of SNF in the near field of a deep geological repository requires process understanding of SNF dissolution and rates, in addition to the quantification of the radionuclide release from SNF under reducing conditions of a breached container. With the aim to derive a radionuclide source term, the SNF dissolution and alteration processes can be assigned to two steps, namely the (i) instantaneous release of radionuclides upon cladding failure from gap and grain boundaries and (ii) a long-term release that results from the dissolution of the fuel grains themselves (Ewing, 2015). Since most radionuclides produced during irradiation of nuclear fuel in a reactor are trapped within the SNF matrix, understanding the processes leading to the dissolution of the matrix and its dissolution rates are of particular interest for post-closure safety assessments (Pastina and LaVerne, 2021). Research at the Institute for Nuclear Waste Disposal (INE) at the Karlsruhe Institute of Technology (KIT) has focused, for more than 25 years, on the behaviour of SNF (irradiated UO2 and mixed-oxide, MOX, fuels) under geochemical conditions (pH, redox milieu, gas atmosphere and ionic strength) representative of various repository concepts and radiolytic reactions on SNF dissolution mechanisms. This contribution will give an overview on the radionuclide release from dissolving SNFs under repository conditions. In particular, uranium released into solution from UO2 and MOX fuels during up to 1629 d of leaching in salt brines, granitic/bentonitic or cementitious groundwaters under Ar or Ar/H2 atmospheres. As observed in other published studies on SNF dissolution under reducing conditions, a large scatter of the uranium concentration is seen in the initial stages of our experiments. After about 1 year of leaching, the aqueous concentration of uranium slowly approaches the solubility limit of U(IV), independent of the type of studied SNF samples (various irradiated UO2 and MOX fuels). A similar behaviour is observed for other redox-sensitive actinides. The release rate of uranium decreases significantly in all experiments within first 400 d of leaching. Although the rate is very low, it is >0, and a continuous release is observed. A comparison of the results from SNF experiments under various redox conditions demonstrates that oxidative matrix dissolution is inhibited due to the presence of hydrogen. Our results are discussed in the context of the outcome of international research programmes on SNF corrosion. These findings are considered to be of relevance for the definition of source terms for various irradiated LWR fuels in safety investigations for a DGR in Germany.

Hydration and response of an experimental Sandwich shaft-sealing system at the Mont Terri rock laboratory

Abstract. A necessary and important component for the closure of deep geological repositories (accessed by a shaft) is a shaft-sealing system that limits the fluid inflow from the adjacent rock to the repository in the early post-closure phase and delays the release of possibly contaminated fluids from the repository at a later stage. The Sandwich system developed at Karlsruhe Institute of Technology (Schuhmann et al., 2009) is a multicomponent barrier that can contribute to this sealing function and is considered as part of the German shaft-sealing concept (Kudla and Herold, 2021). Its functionality has been assessed in a large-scale in situ test (the SW-A experiment) carried out at the Mont Terri rock laboratory (MTRL) in cooperation with international partners as part of the Sandwich-HP project since July 2019. The in situ test was planned as part of an international pre-project (Emmerich et al., 2019) and is accompanied by a laboratory- and semi-technical-scale test program as well as by model simulations. The setup of the SW-A experiment comprises two shafts of 1.18 m diameter and 10–12.6 m depth in the Sandy Facies of the Opalinus Clay at MTRL. Each shaft contains a Sandwich seal as well as a hydration system in order to realize fluid inflow from the bottom (Fig. 1a). The implemented Sandwich system is characterized by an alternating arrangement of four low-permeability sealing segments (DS) made of bentonite and five equipotential segments (ES) made of fine-grained quartz sand with higher hydraulic conductivity. Fluid entering an ES is supposed to be evenly distributed over the cross section and, thus, the interface of the adjacent DS, leading to a homogeneous hydration and swelling of the DS. Water bypassing a DS and high hydraulic loads can be absorbed and distributed by the next ES. In the experiment, the sealing systems and the surrounding rock are intensely monitored (e.g., geophysics, water content, relative humidity and temperature, pore pressure, stress, and displacement) in order to investigate the saturation process and assess the interaction of the sealing system and the host rock. Hydration of the system in Shaft 1 started in May 2021, and the monitoring system showed a relatively fast saturation of the lowermost ES and DS and a water bypass in August 2021 (Fig. 1b); this was accompanied by slower saturation of the upper ES and DS, swelling of the DS and a pore pressure increase in the surrounding rock. Hydration of Shaft 2 started in May 2023. Data and experience obtained to date will be presented.

Experimental investigation of fission gas release from spent nuclear fuels under conditions expected in a deep geological repository

Abstract. In Germany, as well as several other countries (e.g. Sweden, Finland and Switzerland), the disposal of spent nuclear fuel (SNF) in deep geological formations, intertwined with a resilient multi-barrier concept, is considered to be the favourable option for the safe and profound isolation of such wastes from the biosphere. However, the intrusion of groundwater, followed by a failure of canisters and loss of cladding integrity, has to be considered in the long-term evaluation of such an underground repository. Therefore, a thorough process understanding of SNF dissolution, radionuclide source terms and alteration processes is necessary in order to evaluate the performance of SNF in the repository system. The aforementioned processes can be assigned into two steps: (i) a fast, initial release of radionuclides, located in accessible structures of the SNF upon cladding failure, and (ii) a slower, long-term release, resulting from the dissolution of the fuel matrix itself (Ewing, 2015). During the first stages of breaching of the container and the resulting contact of groundwater with the waste form, a fraction of radionuclides, located in easily accessible parts of the SNF such as grain boundaries or the pellet-cladding gap, will be released relatively quickly. This fraction is comprised of mostly volatile radionuclides, such as 79Se, 129I, 135Cs, and the fission gases Kr and Xe. Especially the release of fission gases from SNF is often correlated to the release properties of safety-relevant radioisotopes such as 129I or 135Cs and is, therefore, an indicator of their release rates. In particular, 129I shows a release behaviour similar to the fission gases. Within our contribution, we provide results regarding the release of fission gases during the dissolution process of two different types of SNF, i.e. UOX (50.4 GWd tHM-1) and mixed-oxide (MOX) (38.0 GWd tHM-1, where HM denotes heavy metals) fuels, under simulated geochemical conditions, as they are expected in a deep geological repository. Both examined fuel types were irradiated in commercial pressurised water reactors in Switzerland and Germany during the 1980s. The shown data were compiled over more than a decade during experimental campaigns performed at the Institute for Nuclear Waste Disposal at Karlsruhe Institute of Technology (KIT-INE) within the framework of several international programmes. Results obtained in our study indicate that, independent of the type of SNF, a comparable, fast initial release of fission gases is evident in all experiments. However, throughout the experiments, this prompt release slows down significantly, although a continuous release can be observed. Furthermore, the obtained data on fission gas release are compared to the release behaviour of iodine and caesium. An attempt is made to identify and qualify the role of fission gas release rates as indicator of the radionuclide source term for SNF by comparing and interpreting respective data collected over various experimental campaigns.

X-ray absorption fine structure (XAFS)-based radionuclide research at the KIT Light Source

Abstract. In the past two decades, X-ray absorption spectroscopy (XAS) and related synchrotron-based radionuclide speciation techniques have become indispensable, supporting open issues in fundamental radiochemistry and nuclear waste disposal alike. Physicochemical structure information – encoded in the element-specific X-ray absorption fine structure (XAFS) – is obtained by the precise determination of the linear mass absorption coefficient μ(E) of a specimen in an X-ray energy window ΔE encompassing an electronic bonding level of a selected atom type. The characteristic modulations of μ(E) in the vicinity of an “absorption edge” (i.e., the steeply rising absorption probability of photons tuned to the binding energy of inner shell “core” electrons) are attributed to electronic transitions into unoccupied states due to the photoelectric effect. While absorption features close to the edge (arising from excitations into molecular orbitals or empty band structure levels close to the Fermi level) are generally denoted as an X-ray absorption near-edge structure (XANES), the scattering states at higher excitation energies are causing the well-known extended X-ray absorption fine structure (EXAFS). EXAFS oscillations of the post-edge μ(E) are caused by the periodicity of the constructive and destructive interference of outbound and backscattered inbound photoelectron waves (superimposing at the absorbing atom site) when continuously increasing the excitation energy. Quantitative analysis of EXAFS data based on electron scattering theory is a well-established short-range structural probe, providing precise values of interatomic distances (between the absorber atom and its neighbors) and additional information on the type, number, and ordering of neighbor atoms within a local cluster. Recent significant advancements in the quantum theoretical description of core-excited final states have been successful in overcoming persisting ambiguities in XANES data interpretation. Meanwhile, although there are more than 50 synchrotron radiation centers operational in the world, facilities with specialized beamline infrastructure and safety protocols to allow experiments on radioactive samples with activities beyond the exemption limits are still scarce. At the KIT Light Source (at the Karlsruhe Institute of Technology, Karlsruhe, Germany), the Institute for Nuclear Waste Disposal (Institut für Nukleare Entsorgung, INE) operates two beamline end-stations dedicated to the investigation of radionuclide materials by XAFS spectroscopy and related techniques, i.e., the INE-Beamline (operational since 2005) and the ACT station of the CAT-ACT (CATalysis and ACTinide) wiggler beamline (operational since 2016). Samples with total activities amounting to 1.0×106 times the isotope specific exemption limits and 200 mg of fissile isotopes 235U and 239Pu are feasible at both beamlines. Highly versatile detection systems and sample holders – generally avoiding extensive shielding or sample handling in a glove box – have been conceived since the initial commissioning of the beamlines and have enabled unique XAFS measurements such as the first ever investigation of aqueous technetium species at the Tc L3 edge. Investigations of highly radioactive specimens (e.g., spent nuclear fuel or nuclear waste glass fragments) are feasible, regardless of the actual contact dose rate if the radiation field is limited to a few microsieverts per hour at the edge of the experimental table.

Distance Transform Pooling Neural Network for LiDAR Depth Completion.

Recovering dense depth maps from sparse depth sensors, such as LiDAR, is a recently proposed task with many computer vision and robotics applications. Previous works have identified input sparsity as the key challenge of this task. To solve the sparsity challenge, we propose a recurrent distance transform pooling (DTP) module that aggregates multi-level nearby information prior to the backbone neural network. The intuition of this module is originated from the observation that most pixels within the receptive field of the network are zero. This indicates a deep and heavy network structure has to be used to enlarge the receptive field aiming at capturing enough useful information as most processed signals are uninformative zeros. Our recurrent DTP module can fill in empty pixels with the nearest value in a local patch and recurrently transform distance to reach farther nearest points. The output of the proposed DTP module is a collection of multi-level semi-dense depth maps from original sparse to almost full. Processing this collection of semi-dense depth maps alleviates the network from the input sparsity, which helps a lightweight simplified ResNet-18 with 1M parameters achieve state-of-the-art performance on the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) depth completion benchmark with LiDAR only. Besides the sparsity, the input LiDAR map also contains some incorrect values due to the sensor error. Thus, we further enhance the DTP with an error correction (EC) module to avoid the spreading of the incorrect input values. At last, we discuss the benefit of only using LiDAR for nighttime driving and the potential extension of the proposed method for sensor fusion and the indoor scenario. The code has been released online at https://github.com/placeforyiming/DistanceTransform-DepthCompletion.

CAM-FRN: Class Attention Map-Based Flare Removal Network in Frontal-Viewing Camera Images of Vehicles

In recent years, active research has been conducted on computer vision and artificial intelligence (AI) for autonomous driving to increase the understanding of the importance of object detection technology using a frontal-viewing camera. However, using an RGB camera as a frontal-viewing camera can generate lens flare artifacts due to strong light sources, components of the camera lens, and foreign substances, which damage the images, making the shape of objects in the images unrecognizable. Furthermore, the object detection performance is significantly reduced owing to a lens flare during semantic segmentation performed for autonomous driving. Flare artifacts pose challenges in their removal, as they are caused by various scattering and reflection effects. The state-of-the-art methods using general scene image retain artifactual noises and fail to eliminate flare entirely when there exist severe levels of flare in the input image. In addition, no study has been conducted to solve these problems in the field of semantic segmentation for autonomous driving. Therefore, this study proposed a novel lens flare removal technique based on a class attention map-based flare removal network (CAM-FRN) and a semantic segmentation method using the images in which the lens flare is removed. CAM-FRN is a generative-based flare removal network that estimates flare regions, generates highlighted images as input, and incorporates the estimated regions into the loss function for successful artifact reconstruction and comprehensive flare removal. We synthesized a lens flare using the Cambridge-driving Labeled Video Database (CamVid) and Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago (KITTI) datasets, which are road scene open datasets. The experimental results showed that semantic segmentation accuracy in images with lens flare was removed based on CAM-FRN, exhibiting 71.26% and 60.27% mean intersection over union (mIoU) in the CamVid and KITTI databases, respectively. This indicates that the proposed method is significantly better than state-of-the-art methods.

Monocular Distance Estimation-based Approach using Deep Artificial Neural Network

Those in authority are evaluating the test evaluation for threat assessments currently in place. Since people often depend on their feelings and moods, this may create inequality. Therefore, this study suggested applying deep learning for Autonomous Emergency Steering (AES) and Autonomous Emergency Braking (AEB) assessments in the safety rating protocol. The suggested method for the test in situation-based threat assessments is a monocular distance estimation-based approach. The camera's objective is to make it simple to conduct assessments using only an onboard dash camera. This study proposes a method based on a monocular distance estimation-based approach for test methodology in the situational-based threat assessments using deep learning for the AES system to complement the AEB system for active safety features. Then, the accuracy of the distance estimation models has validated with the ground truth distances from the KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) dataset. Thus, the output of this study can contribute to the methodological base for further understanding of drivers the following behaviour with a long-term goal of reducing rear-end collisions.

The Steady-State ALTADENA RASER Generates Continuous NMR Signals.

The front cover artwork is provided by Dr. Lehmkuhl's group at the Karlsruhe Institute of Technology. The image shows continuous NMR signals complemented by a simulated bifurcation diagram of a nonlinear RASER system. Read the full text of the Research Article at 10.1002/cphc.202300204.

Aerothermal comparison of a diffuser hole and a slot geometry: thermal performance and jet stability

Numerous experimental investigations, predominantly determining the adiabatic film cooling effectiveness and the heat transfer coefficient with film cooling dependent on parameters such as blowing ratio (M), density ratio (DR), velocity ratio (VR) and momentum flux ratio (IR) have been conducted in the past for a vast variety of geometries. To fully characterize a jet in cross-flow for its application in film cooling, thermal and aerodynamic parameters have to be analysed in conjunction. In the present work, detailed flow field measurements using Stereoscopic Particle Image Velocimetry (SPIV) are conducted at engine-realistic operating conditions in a test rig at the Institute of Thermal Turbomachinery (ITS) at the Karlsruhe Institute of Technology (KIT). Additionally, thermal measurements using Infrared Thermography (IRT) are carried out to determine the adiabatic film cooling effectiveness and the heat transfer coefficient with film cooling. Two film cooling hole geometries are analysed: A 10°-10°-10° laidback fan-shaped shaped film cooling hole (LFH10) and a slot geometry with a plenum-like inlet. Flow field data, and thermal film cooling quantities are analysed to quantify and characterize their aero-thermal behaviour. The significance of the stability and continuity of the exiting film cooling jets for the thermal performance is demonstrated to comprehend the differences in how efficiently the provided cooling air is used. It is shown that the absence of the counter-rotating vortex pair may not necessarily lead to an improved adiabatic film cooling effectiveness <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mi>η</mml:mi><mml:mrow><mml:mrow><mml:mi mathvariant="normal">a</mml:mi><mml:mo>,</mml:mo><mml:mi mathvariant="normal">W</mml:mi></mml:mrow></mml:mrow></mml:msub></mml:math></inline-formula>.