Reference Structure Research Articles

Combining ultrasound and microelectrode recordings for postoperative localization of subthalamic electrodes in Parkinson’s disease

ObjectiveTo assess transcranial sonography (TCS) as stand-alone tool and in combination with microelectrode recordings (MER) as a method for the postoperative localization of deep brain stimulation (DBS) electrodes in the subthalamic nucleus (STN). MethodsIndividual dorsal and ventral boundaries of STN (n = 12) were determined on intraoperative MER. Postoperatively, a standardized TCS protocol was applied to measure medio-lateral, anterior-posterior and rostro-caudal electrode position using visualized reference structures (midline, substantia nigra). TCS and combined TCS-MER data were validated using fusion-imaging and clinical outcome data. ResultsTest-retest reliability of standard TCS measures of electrode position was excellent. Computed tomography and TCS measures of distance between distal electrode contact and midline agreed well (Pearson correlation; r = 0.86; p < 0.001). Comparing our “gold standard” of rostro-caudal electrode localization relative to STN boundaries, i.e. combining MRI-based stereotaxy and MER data, with the combination of TCS and MER data, the measures differed by 0.32 ± 0.87 (range, −1.35 to 1.25) mm. Combined TCS-MER data identified the clinically preferred electrode contacts for STN-DBS with high accuracy (Coheńs kappa, 0.86). ConclusionsCombined TCS-MER data allow for exact localization of STN-DBS electrodes. SignificanceOur method provides a new option for monitoring of STN-DBS electrode location and guidance of DBS programming in Parkinson’s disease.

Neutron crystallographic refinement with REFMAC5 from the CCP4 suite.

Hydrogen (H) atoms are abundant in macromolecules and often play critical roles in enzyme catalysis, ligand-recognition processes and protein-protein interactions. However, their direct visualization by diffraction techniques is challenging. Macromolecular X-ray crystallography affords the localization of only the most ordered H atoms at (sub-)atomic resolution (around 1.2 Å or higher). However, many H atoms of biochemical significance remain undetectable by this method. In contrast, neutron diffraction methods enable the visualization of most H atoms, typically in the form of deuterium (2H) atoms, at much more common resolution values (better than 2.5 Å). Thus, neutron crystallography, although technically demanding, is often the method of choice when direct information on protonation states is sought. REFMAC5 from the Collaborative Computational Project No. 4 (CCP4) is a program for the refinement of macromolecular models against X-ray crystallographic and cryo-EM data. This contribution describes its extension to include the refinement of structural models obtained from neutron crystallographic data. Stereochemical restraints with accurate bond distances between H atoms and their parent atom nuclei are now part of the CCP4 Monomer Library, the source of prior chemical information used in the refinement. One new feature for neutron data analysis in REFMAC5 is refinement of the protium/deuterium (1H/2H) fraction. This parameter describes the relative 1H/2H contribution to neutron scattering for hydrogenisotopes. The newly developed REFMAC5 algorithms were tested by performing the (re-)refinement of several entries available in the PDB and of one novel structure (FutA) using either (i) neutron data only or (ii) neutron data supplemented by external restraints to a reference X-ray crystallographic structure. Re-refinement with REFMAC5 afforded models characterized by R-factor values that are consistent with, and in some cases better than, the originally deposited values. The use of external reference structure restraints during refinement has been observed to be a valuable strategy, especially for structures at medium-low resolution.

Modelling Robot Architectures with AADL

Robots are complex systems composed of many interacting subsystems, each coordinating a multitude of hardware and software components. In the last twenty years, robotic frameworks helped accelerate the development process by providing a reference structure and publicly available software components. However, current practices are not sustainable for modern robotic systems. In this work, we present a modelling approach based on the Architecture Analysis and Design Language (AADL) to define robotic systems and enhance software development practices for robotics. Additionally, we exploit the model to perform automatic code generation, which reduces development time and guarantees a more reliable and robust implementation.

Multi-criteria optimization of Cook&amp;Chill processes for network catering establishments

The article presents innovative Cook&amp;Chill technologies, describes the stages of technological production of products. The nature of the technological processes of a catering company is the main factor that determines which types of automated thermal equipment should be used at this enterprise in order to ensure high economic efficiency of its use, facilitate the work of workers engaged in its operation, increase the level of labor automation, the optimization of Cook and Chill processes is shown to be associated with a variety of criteria for choosing the optimal option includes criteria for min deviations from the reference structures: amino acid composition of the product; fatty acid composition; vitamin content; composition of trace elements, as well as criteria for food digestibility, nutritional, biological and energy value of the product. Cook&amp;Chill meets absolutely all the requirements in this regard, allowing you to rationally manage the cost of the product by reducing the cost of producing a dish. The effectiveness of the method has been proven by practical world experience. Cook and Chill technology allows you to increase the yield of batches by three or four times. When preparing dishes, no changes in recipes are required and the current technological standards can be used. Cook and Chill technology can be effectively applied at enterprises with any range of products, up to the widest, and of any capacity. This technology provides for the use of fairly familiar pieces of equipment, such as a convector or microwave oven, air-type intensive cooling systems (blast-chiller) or water-type (tumbler-chiller or turbojet-chiller).

Automated benchmarking of combined protein structure and ligand conformation prediction.

The prediction of protein-ligand complexes (PLC), using both experimental and predicted structures, is an active and important area of research, underscored by the inclusion of the Protein-Ligand Interaction category in the latest round of the Critical Assessment of Protein Structure Prediction experiment CASP15. The prediction task in CASP15 consisted of predicting both the three-dimensional structure of the receptor protein as well as the position and conformation of the ligand. This paper addresses the challenges and proposed solutions for devising automated benchmarking techniques for PLC prediction. The reliability of experimentally solved PLC as ground truth reference structures is assessed using various validation criteria. Similarity of PLC to previously released complexes are employed to judge PLC diversity and the difficulty of a PLC as a prediction target. We show that the commonly used PDBBind time-split test-set is inappropriate for comprehensive PLC evaluation, with state-of-the-art tools showing conflicting results on a more representative and high quality dataset constructed for benchmarking purposes. We also show that redocking on crystal structures is a much simpler task than docking into predicted protein models, demonstrated by the two PLC-prediction-specific scoring metrics created. Finally, we introduce a fully automated pipeline that predicts PLC and evaluates the accuracy of the protein structure, ligand pose, and protein-ligand interactions.

Accurate Matching of a Secondary Amino-Functionality Metal-Organic Cage for Selective Recognition and Supramolecular Binding during Photoinduced Hydrogen Evolution.

Accurate matching of the active sites between the host and guest molecules has a great effect on the selective recognition of different but similar guest molecules or different binding abilities toward the same molecule. Herein, a pseudotetrahedral metal-organic cage (MOC, Co-TAP) that contains secondary amino groups designed as guest-interacting sites was achieved. Co-TAP exhibits the selective recognition of uridine over other similar natural molecules via a fluorescent response. However, a reference structure (Co-TOP) with the same configuration was also synthesized by replacing the secondary amine group with an oxygen atom of the ligand, and it reveals the selective recognition of guanosine. In addition, the accurate matching also enables Co-TAP to strongly bind the organic dye as a guest molecule via host-guest interactions, thus facilitating photoinduced electron transfer between the redox catalytic sites in MOC and the excited guest via a pseudointramolecular pathway.

Maximizing the solar output power using hybrid (CdS/ZnSe) buffer for CIGS thin film solar cell

In this work, a hybrid buffer layer (CdS & ZnSe) is placed between the absorber and the window layer in a CIGS (Copper Indium Gallium Selenide) solar cell replacing the commonly used single-layer CdS. The buffer layer plays a crucial role in interface electricity to enhance the performance of the solar cell. Although, CdS is used as a buffer layer in CIGS solar cells, the toxic nature and parasitic absorption due to the narrowband gap (2.4 eV) become issues during its application in devices. To reduce Cd concentration and ameliorate the bandgap issue, the hybrid buffer layer (CdS & ZnSe) is a perfect supplant. In this study, numerical simulation is performed on CIGS-based solar cells comprised of a hybrid buffer layer to enhance the performance by optimizing the physical parameters (thickness, carrier concentration, and defect density) of both absorber and buffer layer using SCAPS-1D software. In the process of optimizing physical parameters, the effect of the mentioned parameters is observed on the solar cell performance. Later, the impact of working temperature is shown in the solar cell performance. Finally, with all those optimized parameters, a comparison has been done between the reference and the proposed structure. The comparison asserts that the proposed structure with a conversion efficiency of 24.55% is outdistancing the reference structure as well as some relative structures from the recent study. The simulation results in this study can be a didactic one in the fabrication of high-efficiency CIGS solar cells

Guided wave-based cross-scene interfacial debonding detection in reinforced concrete structures

The cross-scene problem within the field of guided wave-based interfacial debonding detection in steel-reinforced concrete structures is a significant challenge. This issue arises when the methods initially designed for laboratory-configured structures or numerical models are adapted to real-world scenarios. In response to this challenge, driven by the concept of domain adaptation, a novel method—the discriminative wavelet adversarial adaptation network (DWAAN)—is proposed to assess the health of analogous structures using diagnostic insights from a reference structure. The proposed method utilizes continuous wavelet transform to segregate signal components. A feature extraction network, designed with the convolutional neural network architecture, extracts domain confusion and damage-sensitive features through guided adversarial adaptive training in the wavelet domain. Both the adversarial and statistical alignment are employed during training for comprehensive optimization of data distribution discrepancies. The effectiveness of the proposed method is assessed in both the homogeneous and heterogeneous cross-scene interfacial debonding detection scenarios, revealing an average performance enhancement of 32.5% in distinct homogeneous applications and 26.6% in heterogeneous scenarios, when compared to the traditional supervised learning approach. In addition, the present method demonstrates robust convergence stability, evidenced by the minimized training fluctuations. The proposed method holds promising potential for practical applications in interfacial debonding detection in reinforced concrete structures while addressing the cross-scene challenge.

Expertise-dependent differences in mental representation metrics of pas de bourrée.

Precise movement control is of prime importance in almost every kind of sport and greatly influences an athlete's performance. In dancing not only motor but also cognitive skills, e.g. in the form of memorized representational structures, are essential components of the performance. This study investigated different metrics related to the long-term memory of ballet dancers with different skill levels regarding the pas de bourrée using the structural-dimensional analysis of mental representations (SDA-M) method. To this end, the Correct Action Selection Probability Analysis (CASPA) algorithm, a recent SDA-M extension that predicts the individual probabilities of correct action selections within a movement sequence, has been applied in the context of dancing for the first time. Significant positive correlations were found between participants' degree of expertise and the proximity of their mental representation structure to the ideal reference structure, as well as between the degree of expertise and the probability of correct action selection within the movement sequence estimated by CASPA. The results indicate that increased training experience in ballet dancing is not only associated with functionally better structured mental representations of the movement sequence but also with a higher probability of correct action selection. These findings provide further evidence for SDA-M with CASPA as an auspicious tool for individualized task-related memory assessments and diagnostics in different action sequences, e.g. as the basis for mental training.

Location of Local Recurrences Post-Prostatectomy Detected by 18F-DCPFyL and Implications for Salvage Radiotherapy Target Volumes.

The use of prostate-specific membrane antigen (PSMA) PET scans have improved detection of recurrent prostate cancer for biochemical failure post-prostatectomy. The primary aim of this study is to assess the location of local recurrences for PSMA PET positive disease post-prostatectomy relative to anatomical landmarks and to inform salvage radiotherapy contouring guidelines. This is a retrospective study of patients who underwent a staging PSMA PET-CT scan with 18F-DCFPyL tracer. Eligible patients included men with biochemical recurrence (PSA >0.2ng/mL) post-prostatectomy for prostate adenocarcinoma. PSMA positive local disease (GTV) was marked on the CT scan of the PSMA PET/CT, using the PSMA PET scan fused as the secondary dataset. Reference structures were contoured to compare the positional relationship to the GTV local recurrence. Centroids of each GTV position were measured to the closest border of the reference structures and distance measured. Forty-five patients had a local recurrence on PSMA PET, 28/45 with prostate bed recurrence and 17/45 with seminal vesicle bed recurrence. The median age was 72.7 years, median pre-treatment PSA 0.515 ng/ml (0.2-11.1), pT2 in 37.8% and pT3 in 62.2, ISUP G2-3 was 66.7%, ISUP 4-5 29.6%, 67% ECE, 15.4% SV involvement and 40% positive margin. For prostate bed recurrences, 93.6% of GTVs were within 15mm from the inferior border of pubic symphysis (median 3.3mm [-9.8-15.4]), 83.9% within 10mm from the VUA (median 3.3mm [-17.4-15.9]), and 80.6% were greater than 10mm from the most superior slice of the penile bulb (median 16.4mm [1-29.5]). Laterally, 83.9% of recurrences were within 10mm of midline and 41.9% within 5mm (median 3.3mm [-13.56-11.59]) and all were contained within levator, 35.5% within 5mm (median 7.7 [1-22.6]) of the medial muscle border. 29.0% were within 5mm from the anterior edge of the rectal wall (median -7mm [-32.3-0.5]). Seminal vesicle bed recurrences were within 17.5mm of upper border of pubic symphysis for 88.9% of patients (median -4.69mm[-30.8to18.2]), 100% were more than 7.5mm inferiorly from the vas deferens (median-22.1mm[-32.7to-7.7]). Laterally, 100% recurrences were more than 7.5mm medial from obturator internus (median 5.37mm [-23.1to37.8]), and 88.9% were more than 10mm from midline (median 23.1mm [2.0-36.6]). The 18F-DCFPyL PSMA PET local recurrences can provide detailed localization of prostate bed and seminal vesicle recurrences. Our data can inform contouring guidelines for salvage radiotherapy to the prostate bed, particularly when using anatomical landmarks to define cranio-caudal extent of target volumes. For target volume laterally, the medial wall of levator ani would encompass all prostate bed recurrences, and no seminal vesicles recurrences were seen at the medial border of the obturator internus muscle.

Predicting the martensitic transition temperatures in ternary shape memory alloys Ni0.5Ti[formula omitted]Hf[formula omitted] from first principles

Martensitic transition temperatures (MTTs) can be tuned by alloying binaries with other elements to create multi-component shape memory alloys (SMAs). However, it is inefficient to use the trial-and-error approach to find compositions with desirable operating temperatures because of the large number of combinations of metals possible to form ternaries, quaternaries, etc. Thus it is crucial to develop the theoretical capability of accurately predicting MTTs as a function of composition, in order to provide experimentalists with necessary and reliable guidance. Previous work has focused on developing and applying first-principles methods to compute phase transitions and MTTs in binary SMAs such as NiTi (nitinol), but certain technical problems associated with the multi-component SMAs remain unsolved. In this work, we employed ab initio molecular dynamics (MD) and thermodynamics integration to study the NiTiHf-based high-temperature ternary SMAs. We overcome the technical challenges to accurately obtain the Gibbs free energy in cubic ternaries where the reference structures are unknown. Specifically, we examined the cubic, monoclinic and orthorhombic structures of Ni0.5Ti0.5−xHfx for x∈[0,0.5], and our results suggest that the cubic-to-monoclinic martensitic transition occurs when x<0.08, for x>0.17 the martensitic transition is between the cubic and orthorhombic phases, whereas in between our calculations cannot distinguish these two martensite structures near the MTT. The computed MTTs vs Hf content x are in good agreement with measured data. Thus our current work paves the way for computational design of multi-component SMAs with desired properties.

Effect of metallurgical step-graded quantum barrier on the performance of InGaN-based laser diode

In this paper, a metallurgical step-graded uniform quantum barrier (QB) laser diode (LD) structure is proposed, which leads to performance enhancement in terms of reduced electron seepage current, reduced threshold current, diminished polarization charges at interfaces, and increased laser power, hole injection efficiency, optical confinement etc. The proposed LD structure demonstrated the best results among all the three structures considered in this study. The laser output power was increased from 118 mW to 160 mW in the metallurgical step-graded uniform QB LD structure as compared to the ungraded QB reference structure. The optical confinement was improved from 0.94% to 1.09% in the photon-generating region. The electron potential barrier height has increased from 191 meV to 242 meV, while the hole potential barrier height has decreased from 133 meV to 116 meV at 120 mA injection current. In addition, the electron seepage flux has reduced from 1374 A cm−2 to 768 A cm−2 at 120 mA injection current.

GelMap: intrinsic calibration and deformation mapping for expansion microscopy

Expansion microscopy (ExM) is a powerful technique to overcome the diffraction limit of light microscopy by physically expanding biological specimen in three dimensions. Nonetheless, using ExM for quantitative or diagnostic applications requires robust quality control methods to precisely determine expansion factors and to map deformations due to anisotropic expansion. Here we present GelMap, a flexible workflow to introduce a fluorescent grid into pre-expanded hydrogels that scales with expansion and reports deformations. We demonstrate that GelMap can be used to precisely determine the local expansion factor and to correct for deformations without the use of cellular reference structures or pre-expansion ground-truth images. Moreover, we show that GelMap aids sample navigation for correlative uses of expansion microscopy. Finally, we show that GelMap is compatible with expansion of tissue and can be readily implemented as a quality control step into existing ExM workflows.

Enhancing energy efficiency and cost-effectiveness while reducing CO2 emissions in a hospital building

Global population growth drives fossil fuel usage, surpassing natural greenhouse gas emissions and causing climate change, higher temperatures, floods, and agricultural erosion. The study underscores the significance of appropriate material selection and meticulous building design to establish a healthy living environment and mitigate energy consumption. The research is dedicated to the reduction of CO2 emissions. Hospitals, due to their constant energy requirements, require optimal temperature and comfort management for patients, necessitating careful design to avoid disruptions and power outages. The principal objective of this research is to enhance energy efficiency in the design phase of hospital buildings in Turkey and to develop an energy-efficient hospital model. This objective is achieved by evaluating different insulation materials, building orientations, lighting efficiency, and window-to-wall ratios. The methodology involves creating a reference structure for energy load calculations using Revit software and utilizing the Green Building Studio (GBS) program to conduct energy analyses in 7 different cities across Turkey. The study found that the utilization of building parameters with renewable energy sources reduced energy consumption by 57.5%, total costs by 16.24%, and CO2 emissions by 26.3%. The fundamental contribution of this study is to demonstrate the feasibility of reducing energy consumption, costs, and CO2 emissions through design adjustments. The novelty of this research lies in its comprehensive approach to optimizing energy efficiency and CO2 emissions in hospital buildings in Turkey. These findings underline the significance of energy-efficient design, particularly considering the impact of increased energy usage and CO2 emissions during the COVID-19 pandemic.

Optimization of the thermal management system of battery thermal network model based on coupled liquid cooling of phase change materials

Battery optimization models can extend battery life, improve safety, and maximize battery performance. Previous optimization methods focus more on (Computational Fluid Dynamics) CFD and data mining. However, the two optimization methods apply only to specific battery module structures. In addition, previous studies have focused more on improving optimization algorithms to improve performance, but the computational design of large-scale battery thermal management systems still requires large loads. This paper presents a new optimization method based on the thermal equivalent circuit model (TECM) of battery thermal management system (BTMS) for the efficient design of liquid-cold coupled phase change material BTMS (PCM). The method can easily change and optimize the battery module structure according to different application scenarios. Compared with the reference structure, the TECM Parto solution optimized combined with multi-objective particle swarm optimization (MOPSO) saved 39.51 % of the liquid cooling energy consumption, reduced the maximum temperature rise of BTMS by 0.38 °C, and reduced the maximum temperature difference by 19.81 %. The method adopted can improve the efficiency and quality of BTMS design, reduce the cost of trial and error, and speed up the design process.

Automated evaluation for rapid implementation of knowledge-based radiotherapy planning models.

Knowledge-based planning (KBP) offers the ability to predict dose-volume metrics based on information extracted from previous plans, reducing plan variability and improving plan quality. As clinical integration of KBP is increasing there is a growing need for quantitative evaluation of KBP models. A .NET-based application, RapidCompare, was created for automated plan creation and analysis of Varian RapidPlan models. RapidCompare was designed to read calculation parameters and a list of reference plans. The tool copies the reference plan field geometry and structure set, applies the RapidPlan model, optimizes the KBP plan, and generates data for quantitative evaluation of dose-volume metrics. A cohort of 85 patients, divided into training (50), testing (10), and validation (25) groups, was used to demonstrate the utility of RapidCompare. After training and tuning, the KBP model was paired with three different optimization templates to compare various planning strategies in the validation cohort. All templates used the same set of constraints for the planning target volume (PTV). For organs-at-risk, the optimization template provided constraints using the whole dose-volume histogram (DVH), fixed-dose/volume points, or generalized equivalent uniform dose (gEUD). The resulting plans from each optimization approach were compared using DVH metrics. RapidCompare allowed for the automated generation of 75 total plans for comparison with limited manual intervention. In comparing optimization techniques, the Dose/Volume and Lines optimization templates generated plans with similar DVH metrics, with a slight preference for the Lines technique with reductions in heart V30Gy and spinal cord max dose. The gEUD model produced high target heterogeneity. Automated evaluation allowed for the exploration of multiple optimization templates in a larger validation cohort than would have been feasible using a manual approach. A final KBP model using line optimization objectives produced the highest quality plans without human intervention.

Natural reference structures for three-dimensional maxillary regional superimposition in growing patients

BackgroundAssessment of growth-related or treatment-related changes in the maxilla requires a reliable method of superimposition. Such methods are well established for two-dimensional (2D) cephalometric images but not yet for three-dimensions (3D). The aims of this study were to identify natural reference structures (NRS) for the maxilla in growing patients in 3D, opportunistically using orthodontic mini-screws as reference; and to test the applicability of the proposed NRS for maxillary superimposition by assessing the concordance of this approach with Björk’s ‘stable reference structures’ in lateral projection.MethodsThe stability of the mini-screws was tested on longitudinal pairs of pre- and post-orthodontic cone-beam computed tomography (CBCT) images by measuring the distance changes between screws. After verifying the stability of the mini-screws, rigid registration was performed for aligning the stable mini-screws. Then, non-rigid registration was used to establish the dense voxel-correspondence among CBCT images and calculate the displacement of each voxel belonging to the maxilla relative to the mini-screws. The displacement vectors were transformed to a standardized maxillary template to categorize the stability of the internal structures statistically. Those voxels that displaced less relative to the mini-screws were considered as the natural reference structures (NRS) for the maxilla. Test samples included another dataset of longitudinal CBCT scans. They were used to evaluate the applicability of the proposed NRS for maxillary superimposition. We assessed whether aligning the maxilla with proposed NRS is in concordance with the maxillary internal reference structures superimposition in the traditional 2D lateral view as suggested by Björk. This was quantitively assessed by comparing the mean sagittal and vertical tooth movements for both superimposition methods.ResultsThe stability of the mini-screws was tested on 10 pairs of pre- and post-orthodontic cone-beam computed tomography (CBCT) images (T1: 12.9 ± 0.8 yrs, T2: 14.8 ± 0.7 yrs). Both the loaded and the unloaded mini-screws were shown to be stable during orthodontic treatment, which indicates that they can be used as reference points. By analyzing the deformation map of the maxilla, we confirmed that the infraorbital rims, maxilla around the piriform foramen, the infrazygomatic crest and the hard palate (palatal vault more than 1 cm distal to incisor foramen except the palatal suture) were stable during growth. Another dataset of longitudinal CBCT scans (T1: 12.2 ± 0.63 yrs, T2: 15.2 ± 0.96 yrs) was used to assess the concordance of this approach with Björk’s ‘stable reference structures’. The movement of the maxillary first molar and central incisor showed no statistically significant difference when superimposing the test images with the proposed NRS or with the classic Björk maxillary superimposition in the lateral view.ConclusionsThe infraorbital rims, maxilla around the piriform foramen, the infrazygomatic crest and the hard palate (palatal vault more than 1 cm posterior to incisal foramen except the palatal suture) were identified as stable regions in the maxilla. These stable structures can be used for maxillary superimposition in 3D and generate comparable results to Björk superimposition in the lateral view.

Learning hyperparameter predictors for similarity-based multidisciplinary topology optimization

Topology optimization (TO) plays a significant role in industry by providing engineers with optimal material distributions based exclusively on the information about the design space and loading conditions. Such approaches are especially important for current multidisciplinary design tasks in industry, where the conflicting criteria often lead to very unintuitive solutions. Despite the progress in integrating manufacturing constraints into TO, one of the main factors restricting the use of TO in practice is the users’ limited control of the final material distribution. To address this problem, recently, a universal methodology for enforcing similarity to reference structures in various TO methods by applying scaling of elemental energies was proposed. The method, however, requires an expensive hyperparameter sampling, which involves running multiple TO processes to find the design of a given similarity to a reference structure. In this article, we propose a novel end-to-end approach for similarity-based TO, which integrates a machine learning model to predict the hyperparameters of the method, and provide the engineer, at minimal computational cost, with a design satisfying multidisciplinary criteria expressed by the similarity to a reference. The training set for the model is generated based on an academic linear elastic problem, but the model generalizes well to both nonlinear dynamic crash and industrial-scale TO problems. We show the latter by applying the proposed methodology to a real-world multidisciplinary TO problem of a car hood frame, which demonstrates the usefulness of the approach in industrial settings.

Optimisation of the damping properties of steel structures using adhesively bonded joints

AbstractAdhesives offer both good damping properties and very high strengths. The possibilities for using the positive damping properties in particular to optimise dynamically stressed steel structures have rarely been explored to date. In this paper, comprehensive numerical and experimental investigations are presented. In numerical investigations on dynamically loaded, representative steel structures, the potential for damping of structures by adhesively bonded joints is analysed. Numerical investigations show that the vibration amplitudes of adhesively bonded structures are more than 95 % lower than those of welded reference structures in the relevant resonance case. Based on this, the damping properties of adhesively bonded tubular steel joints in a scale relevant for construction industry were experimentally investigated. Different geometry and test boundary conditions are investigated in a parameter study. The loss factor of tubular joints is a maximum of 0.38, which is relevant for steel construction. Based on the results of experimental investiga‐tions, a methodology is presented for the analytic determination of the damp‐ing properties of adhesively bonded tubular joints for various specimen ge‐ometries and stress boundary conditions. For this purpose, dimensional anal‐ysis is carried out using the Buckingham Pi Theorem.

Device modelling and optimization of various n-i-p configurations for MASnI3 perovskite solar cells to achieve high efficiency using Solar Cell Capacitance Simulator-1D

Perovskite materials are potential light harvesters, and in specific tin-based absorbers such as methyl ammonium tin iodide (MASnI3) are non-toxic with distinguished optoelectronic properties. This is the first simulation report to explore the application of strontium titanate (SrTiO3) as an electron transport layer (ETL) in planar n-i-p MASnI3 perovskite solar cell (PSC) device. In an attempt to enhance the output performance of MASnI3 PSCs, a systematic approach is devised to determine appropriate alternative charge-selective materials via solar cell capacitance simulator (SCAPS-1D) software. The significance of varying thickness, donor doping concentration, acceptor doping concentration, defect density, diffusion length, and energy band offset for the reference PSC configuration TiO2/MASnI3/Spiro-OMeTAD are investigated. The optimized reference structure delivered 19.72% efficiency. In pursuit of high photovoltaic performance, seven different electron transport materials were comparatively examined. As a result, PCBM, In2S3, and CeO2 were considered not suitable due to their limited electrical performance. Consequently, seven inorganic hole transport layers (HTL) along with four suitable ETL were utilized in MASnI3 PSC to construct twenty-eight novel n-i-p device structures whose efficiency ranges between 14.20% and 22.77% respectively. The influence of varying the work function of back contact, series resistance, shunt resistance, and temperature on the photovoltaic parameters was analysed. The vital parameters investigated in this simulation for implementing state-of-the-art PCS are energy band offset, diffusion length, activation energy, recombination current profile, and built-in-potential. The device configuration featured with SrTiO3/MASnI3/CuO and SrTiO3/MASnI3/MASnBr3 achieved a maximum efficiency of 22.77% and 22.60%, respectively. The PSC tailored with SrTiO3 have better thermal stability and enhanced fill factor, which accounts for improving the output power. These novel findings of all-inorganic PSC will provide preliminary support for practical implementation.