bluuebunny/crossref_metadata_2025 huggingface dataset:
Differences in Microplastic Content in Commercial Salt and Salt at the Semiringkai Coastal Local Center in Kupang City and Kupang Regency
Authors: Dapa Taka Anna Stephanie Mengga , Lada Christina Olly , Amat Anita Lidesna Shinta
Published: April 2023

Background:

Plastic waste that ends up in the ocean can undergo a degradation process into small plastic particles measuring 5 mm called microplastics. The presence of microplastics in the sea can contaminate marine products such as sea salt. Microplastics in the salt consumed by humans can cause adverse health effects. This study aims to determine the difference in the content of microplastics in commercial salt and local salt from the semiringkai coast in Kupang City and Kupang Regency.

Material and Methods:

This research is an observational analytical study with a comparative analysis design. The method used is laboratory observation using a microscope. This study used 10 salt samples which were divided into 2 groups, namely the commercial salt group and the local salt group, each consisting of 5 salt samples. Samples were taken using non-probability sampling method with purposive sampling technique. Data were analyzed univariately and bivariately using the independent T-comparison test.

Results:

The results of the analysis test in this study were P = 0.065 (P > 0.05).

Conclusion:

There is a content of microplastic in commercial salt and local center salt of the semiringkai coast in Kupang City and Kupang Regency with an average that is not significantly different.
Acute Ischemic Stroke with Cortical Blindness Caused by Inherited Protein C Deficiency
Authors: Yu Ching-Hao , Liu Yi , Wang Chih-Wei , Yang Fu-Chi
Published: April 2023

Bilateral occipital lesions caused by bilateral posterior cerebral artery (PCA) blockage are rare and can present as cortical blindness, which is defined as loss of vision without any ophthalmological cause and retention of normal pupillary light reflexes. Inherited protein C (PC) deficiency may cause thromboembolism, which leads to stroke. We presented a 68-year-old man with bilateral hemianopia, and brain imaging revealed bilateral PCA territory infarcts. PC deficiency was identified, and the symptoms gradually resolved after aspirin and warfarin were administered. The patient's family members underwent laboratory examinations, and his daughter was found to have PC deficiency.
Factors Associated with Prolonged Intensive Care Unit Treatment and Organ Failure in Pediatric Patients with Diabetic Ketoacidosis
Authors: Whang Jeffrey Eli , Wu Yi-Lei , Chen Jia-Yuh , Kor Chew-Teng , Lee Ming-Sheng
Published: April 2023

Context:

Patients with diabetic ketoacidosis (DKA) have potential complications, such as respiratory failure, cerebral edema, or acute renal injury, all of which can lead to a prolonged hospital course.

Aims:

This study identified risk factors for prolonged intensive care unit (ICU) stay and organ failure in pediatric patients with DKA.

Materials and Methods:

Patients with DKA aged <19 years admitted to the pediatric ICU of our hospital between June 2011 and May 2021 were enrolled. Demographic characteristics, initial Glasgow Coma Scale score, source of admission, biochemical values, ICU length of stay (LOS), and hospital LOS were collected. The primary outcome was to identify factors associated with prolonged (≥48 h) ICU treatment. The secondary outcomes were to identify factors associated with respiratory failure, cerebral injury, or acute renal failure.

Results:

This study enrolled 137 patients. Nonemergency room admission was associated with longer ICU LOS [adjusted odds ratio (aOR), 3.14; 95% confidence interval (CI) 1.01–9.82] compared with admission from the emergency room. Older age (aOR, 0.89; 95% CI, 0.80–0.99) and underweight (aOR, 0.33; 95% CI, 0.12–0.95) were associated with shorter ICU LOS.

Conclusions:

Recognizing the risk factors associated with prolonged ICU LOS in pediatric patients with DKA may help clinicians with the early identification of critical DKA cases.
Evaluation of continuous wound infusion with local analgesics in postoperative renal transplantation patients
Authors: Alshuaibi Muaath Khaled , Khogeer Abdulghani , Ambusaidi Hamed , Mazeaud Charles , Larose Clement , Lecoanet Pierre , Urmès Isabelle , Lagrange Francois , Lemelle Jean-Louis , Manuguerra Anthony , Fuchs-Buder Thomas , Hubert Jacques , Eschwège Pascal
Published: April 2023

Objectives:

The objective is to evaluate the efficacy of the continuous wound infusion (CWI) with Ropivacaine (naropeine 2 mg/ml) on postoperative pain, analgesics consumption, and bowel function in renal transplantation patients.

Materials and Methods:

A retrospective study trial including 79 patients who underwent renal transplantation. Patients were separated into two groups (catheter or without catheter). We identified 52 (65.8%) patients who received catheter wound infusion during the first 48 h postoperatively. On the other hand, 27 (34.1%) patients received standard without catheter anesthetic technique. Catheter wound infusion was achieved through a 12 cm catheter, inserted subcutaneously after abdominal closure. The catheter was placed above the external oblique aponeurosis. All postoperative data were examined to evaluate the first postoperative 48 h. This study aims to assess three variables: postoperative pain analysis through a visual analog scale, analgesics consumption, and bowel function.

Results:

The overall score of the three variables was studied. Regarding pain assessment, we have determined that the group of patients with catheter scored better than patients without catheter with borderline significance (66.3 vs. 61.2 consecutively; P = 0.0843). An early bowel function was noted in patients with catheters on the 2nd postoperative day (P = 0.0209). Moreover, patients without catheter consumed more painkillers with nonsignificant difference (P = 0.2499).

Conclusion:

Patients with catheter showed earlier bowel function than the noncatheter group on the 2nd postoperative day. The catheter group had better pain evaluation.
A rare presentation of medullary thyroid cancer metastasis to the prostate in a patient with multiple endocrine neoplasia 2B syndrome treated with laparoscopic radical prostatectomy
Authors: Spinos Theodoros , Ermidis Dimitrios , Zabaftis Christos , Nikitakis Filippos , Grivas Nikolaos , Karavitakis Markos
Published: April 2023

Multiple endocrine neoplasia (MEN) syndromes are rare and potentially malignant hereditary entities. Clinical manifestations of MEN 2B include medullary thyroid cancer, pheochromocytoma, gastrointestinal ganglioneuromatosis, and musculoskeletal and ophthalmologic lesions. Metastases to the prostate from the cancers of other organs are extremely rare. There are only a few cases of metastases to the prostate gland, originating from medullary thyroid cancer, found in literature, especially associated with MEN 2B syndrome. In this case report, we present the extremely rare case of a 28-year-old patient, diagnosed with MEN 2B syndrome, with medullary thyroid cancer metastasis to the prostate. Although a few reports of medullary thyroid cancer metastasis into the prostate gland can be found in the literature, to our knowledge, this is the first case of a laparoscopic radical prostatectomy procedure performed as a metastasectomy to treat the prostatic metastasis. Laparoscopic radical prostatectomy, performed as a metastasectomy, for the treatment of metastatic cancer, is an extremely rare surgical indication with distinctive requirements and difficulties. The extraperitoneal access enables the realization of the laparoscopic radical prostatectomy procedure even in the cases of patients with a history of multiple intra-abdominal operations.
Safety of transurethral resection of large prostate
Authors: Al-Bakri Ayman , Al-Jaser Abdullah , Al-Gamdi Khalid , Al-Reshaid Reshaid , Al-Enizi Abdullah , Al-Kharji Ali Ali , Al-Zahrani Ibrahim , Al-Modahi Nawaf , Al-Harbi Moath , Al-Mani Abdullah
Published: April 2023

Background:

Benign prostatic hyperplasia is a common benign disease occurs in older men. Some patients can be treated medically but eventually, most of them will need a surgical intervention, and the most commonly applied procedure is transurethral resection of the prostate (TURP).

Objectives:

The objective of this study is to assess the feasibility and safety of performing transurethral resection of large prostate (80 g and more).

Methodology:

Out of 153 patients reviewed 48 cases included in this study. The main data collected from patients’ files and patient interview. The criteria of exclusion were prostate size <80 g and previous history of TURP. The collected data were analyzed by the Statistical Package for the Social Sciences (SPSS).

Results:

The main results showed that 93.7% of patients did not experience major bleeding postoperatively, neither major drop in hemoglobin level. Moreover, the patient’s distribution according to the presence of TUR syndrome was only 2.1% with mild symptoms. No patient had an episode of retention during the hospital stay or in the follow-up.

Conclusion:

Surgeon experience, systematic resection approach, and strict time of resection are important factors to assure the safety of TURP in large prostate. In cases of huge prostate size >100 g, staged TURP can be offered safely or if patients’ obstructive symptoms do not resolve after the first procedure.
Time of onset and factors associated with delayed response post intradetrusor injection of onabotulinumtoxin a in patients with neurogenic and idiopathic overactive bladder syndrome
Authors: Al-Shaiji Tariq Faisal , Al-Yousef Rawan Jamal , EL-Nahas Ahmed Refat , Awad Awad Thahir , Almutairi Meshari Falah , Al-Terki Abdullatif Ebrahim
Published: April 2023

Objective:

The objective of this study was to determine risk factors for delayed response in patients with neurogenic and idiopathic overactive bladder (OAB) after intradetrusor onabotulinumtoxin A injection.

Subjects and Methods:

This is a retrospective study that included 87 patients who underwent onabotulinumtoxin A intradetrusor injection from October 2011 to November 2019. Patients were followed up at 2, 4, and 12 weeks post intervention in the outpatient clinic and over the phone. The data of patients with early response were compared with those with late response using univariate and multivariate analyses.

Results:

The study included 87 patients. The mean age was 41 ± 15.3 standard deviation, and 69% of the participants were female. Fifty-one percent were diagnosed with neurogenic OAB. A median response time to onabotulinumtoxin A injection of 7 days was demonstrated, and patients who responded during the first 7 days post procedure were considered early responders. Independent predictors for late response include diabetes (Relative risk: 3.89, P = 0.018, and 95% confidence interval [CI]: 1.26–11.98), >1 BTX-A session (Relative risk: 4, P = 0.011, and 95% CI: 1.38–11.6), and wet OAB (RR: 9.94, P = 0.002, and 95% CI: 2.31–42.17).

Conclusions:

The median time of onset post intradetrusor injection of onabotulinumtoxin A was found to be 7 days. Diabetes mellitus, wet OAB, and <1 Botox sessions were independent risk factors for late onset of response.
A mathematical method to estimate angle and distance for percutaneous renal puncture based on computed tomography data
Authors: Salem Shady Mohamed , Aldousari Saad A
Published: April 2023

Introduction:

Gaining access to the kidney is crucial step in percutaneous nephrolithotomy (PCNL); it has a steep learning curve.

Objective:

Describe the mathematical method to predict renal puncture angle and distance based on preoperative computed tomography (CT) measurements. Then evaluating how it correlates with measured values.

Patients and Methods:

The study was prospectively designed. After ethical committee approval, the study uses data from preoperative CT to construct a triangle so we can estimate puncture depth and angle. A triangle of three points, the first is point of entry to the pelvicalyceal system (PCS), the second is point on the skin perpendicular to it, and the third where the needle punctures the skin. The needle travel is estimated using the Pythagorean theorem and puncture angle using the inverse sine function. We evaluated 40 punctures in 36 PCNL procedures. After PCS puncture using fluoroscopy-guided triangulation, we measured the needle travel distance and angle to the horizontal plane. Then compared the results with mathematically estimated values.

Results:

We targeted posterior lower calyx in 21 (70%) case. The correlation between measured and estimated needle travel distance with Rho coefficient of 0.76 with P < 0.001. The mean difference between the estimated and the measured needle travel was – 0.37 ± 1.2 cm (−2.6–1.6). Measured and estimated angle correlate with Rho coefficient of 0.77 and P < 0.001. The mean difference between the estimated and the measured angle was 2° ± 8° (−21°–16°).

Conclusion:

Mathematical estimation of needle depth and angle for gaining access to the kidney correlates well with measured values.
Bladder cancer in young adults
Authors: Albakri Mahmoud , Abu-Hijlih Ramiz , Salah Samer , Al-Ibraheem Akram , Abuhijla Fawzi , Serhan Hashem Abu , Farkouh Ala’a , Obeid Zeinab , Shahait Mohammed
Published: April 2023

Objectives:

The incidence of bladder cancer in the Middle East is increasing. Nevertheless, data on the young population with urothelial carcinoma (UC) of the urinary bladder in this region is scarce. Therefore, we evaluated clinical and tumor characteristics, in addition to treatment details in patients younger than 45 years old.

Methodology:

We reviewed all patients presenting with UC of the urinary bladder from July 2006 to December 2019. Clinical characteristics including demographics, stage at presentation, and treatment outcomes were extracted.

Results:

Out of 1272 new cases of bladder cancer, a total of 112 (8.8%) patients were ≤45 years old. Seven patients (6%) had nonurothelial histology and were excluded from the study. The remaining 105 eligible patients with UC had a median age at presentation of 41 years (35–43). Ninety-three patients (88.6%) were males. Tumor stage at presentation: nonmuscle invasive disease (Ta-T1), locally advanced muscle-invasive bladder cancer (MIBC) (T2-3), and metastatic disease were 84.7%, 2.8%, and 12.5%, respectively. All patients with MIBC received neoadjuvant cisplatin-based chemotherapy. Radical cystectomy was performed in 8 (7.6%) cases; three patients with MIBC and five with high-volume non-MIBC. Neobladder reconstruction was done in six patients. A total of 13 patients with metastatic disease (93%) received palliative chemotherapy (gemcitabine/cisplatin), and one (7%) was a candidate for best supportive care only.

Conclusion:

Bladder cancer is relatively rare in the young population, although the incidence at our region is higher than other reports in the literature. Most patients present with early disease. Early diagnosis and multidisciplinary approach are paramount for the management of these patients.
Upstream Disturbance Effects on Self-Similarity in the Wake of a DrivAer Model
Authors: Rallapalli Anurag , Proenca Anderson , Garry Kevin
Published: April 2023

This study aims to provide an understanding of self-similarity in the turbulent wake generated by a Fastback DrivAer automotive model and assess the impact of upstream disturbances on the wake. The disturbances are generated using a circular cylinder placed five cylinder diameters upstream. Multiple ‘cylinder-model’ positions were tested by offsetting the lateral positioning of the cylinder with respect to the centreline of the model. Data was obtained at cross-planes in the wake going from 25% to 100% car length. Wind tunnel data has been obtained using a total pressure probe rake and a four-hole cobra probe. Data has also been obtained using RANS based simulations with k – ε realisable turbulence model. Mean axial-component velocity profiles were analysed with momentum thickness (θ) and vorticity thickness (δω) used as the scaling parameters. It was seen that self-similarity marginally exists in the wake depending on the upstream conditions and the scaling parameter. Overall, vorticity thickness was seen to be better. Downstream, the mean profiles show a simpler collapse compared to the near wake. Understanding how deficit decay takes effect in the wake is useful to improve the aerodynamic performance of an automobile/motor car/ground vehicle. Therefore, establishing the similarity parameters presented in the work is an early step towards an analytical description of a turbulent wake model.
Research on the Automobile Aerodynamic Field at the Politecnico di Torino in the Second Half of the Twentieth Century
Authors: Nuccio Patrizio
Published: April 2023

With this paper the author first of all wants to honor the memory of Professor Alberto Morelli with whom he had the privilege of working for many years at the Politecnico di Torino. Morelli radically changed the way of designing car body shapes, while bringing the aspect of reducing the aerodynamic resistance of a vehicle to the attention of car designers. Morelli’s research activity began in the early 1950s and, between the 1950s and 1960s, he designed and built a number of car prototypes, whose coefficient of aerodynamic resistance was substantially reduced compared to that of the cars of that time, sometimes resorting to revolutionary architectures such as a “diamond” arrangement of the wheels. A fundamental step of Morelli's research in the field of vehicle aerodynamics was the Pininfarina full-scale wind tunnel project, which was set up between the end of the 1960s and the beginning of the 1970s, and was inaugurated in 1972: fifty years have therefore passed since that occasion. An impressive result, obtained in the second half of the 1970s, was the maquette of the Pininfarina-CNR car, which had front air intakes, internal flows as well as other external details, such as rear-view mirrors: in this case, the Cx value was 0.20. His activity continued with significant results in the field of car aerodynamics, in particular concerning the interaction between the wakes of the car and of the wheels.
Rolling Resistance and Wet/Snow Traction Performance of Commercially Available Light-Duty Vehicle Tires in North America (Canada) Pt.II
Authors: Shafique Hamza , Conde Aaron , Beaupre-Jacques Anthony
Published: April 2023

Low rolling resistance tires are a technology used to improve fuel economy and reduce greenhouse gas emissions in the transportation sector. This project analyzed current relationships between environmental and safety performance properties of commercially available light-duty tire models in Canada. This paper presents the results of a blinded multi-year light-duty vehicle tire research project conducted by Transport Canada & Natural Resources Canada. The study follows on an update to SAE WCX 2018-01-1336 which presented results for tires tested between MY2014-2018. Tire performance was evaluated in a variety of tire categories with a focus on wet grip and rolling resistance. Correlations between key performance indicators were charted to analyze trends in new model tires available on the Canadian tire market. Manufacturer specifications were also charted to evaluate the relations of wet grip and rolling resistance with price, UTQG ratings, and marketing categories. Testing for rolling resistance was done using the single point rolling resistance coefficient method via ISO 28580. Wet grip index values were measured as a metric of performance through UNECE Reg.117, with snow and ice performance ratings from ASTM 1805. The data presented in the following paper provides empirical insight into the light-truck, “new generation” winter tire market, original equipment manufacturer tire (OEM), and an assorted winter tire testing campaign. Important context was added in these markets, to provide regulators with information that can be used to assess a potential minimum energy performance standard (MEPS) for replacement passenger tires in support of policy goals. 155 unique model tires were tested within the 2018-2022 campaign further adding to the 138 presented in the previous edition of this paper (SAE WCX 2018-01-1336).
Multi-Joint Topology Optimization: An Effective Approach for Practical Multi-Material Design Problems
Authors: Sirola Tim , Hardman Andrew , Morris Zane , Huang Yuhao , Shi Yifan , Kim Il Yong , Pamwar Manish , Sangha Balbir
Published: April 2023

With the recent push for electrification, automotive engisneers are constantly striving to improve efficiency and performance of vehicle concepts. Although multiple vehicle attributes affect range, the overall mass of the vehicle plays a significant role. Computational tools such as topology optimization (TO) have long been utilized in industry to reduce mass while meeting structural design constraints. Over time, TO methods have been extended from traditional single material topology optimization (SMTO) to advanced methods such as multi-material topology optimization (MMTO). These advanced computational tools provide more design freedom in the conceptual design phase to develop superior load paths not possible with SMTO. However, MMTO is limited by the assumption of perfect joining between dissimilar materials, requiring manual re-interpretation to develop manufacturable designs. Multi-joint topology optimization (MJTO) has been developed to incorporate material joining within the optimization loop, producing designs which require less manual interpretation. In this paper, an improved MJTO methodology is presented which aims to address limitations of previous methods. Here, the MJTO problem is extended to consider multiple joint materials and joint cost responses in unstructured meshes. A complete review of the improved method, including all related material interpolation schemes and sensitivity expressions is presented with reference to fundamental concepts of SMTO and MMTO. Issues from previous methods are highlighted throughout to provide background and support the rationale behind the new approach. A modified interface detection method and a novel combined filtering scheme are introduced to improve interface quality and convergence stability issues from previous implementations. In the last section, multiple case studies are presented to demonstrate the capability of the improved MJTO approach for 2D and 3D unstructured meshes. MJTO results are compared to MMTO solutions for equivalent problems, and the implications of including material joining within the optimization loop are discussed.
Efficient Design of Automotive Structural Components via De-Homogenization
Authors: Najmon Joel , Tovar Andres
Published: April 2023

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization. To address these issues, this paper presents an efficient de-homogenization method that can be applied to any macroscale topology in order to obtain a high-fidelity multiscale structure. In contrast to prior de-homogenization methods, an alternative representation of the rectangular hole microstructure is proposed so that it is only dependent on the local density and stress distributions. Consequently, MSTO methods are not needed for the de-homogenization method to be applied. This makes the method applicable to any conceptual design, including those from simple single-scale TO codes. Additionally, the proposed de-homogenization method avoids the expensive mapping optimization problem associated with most projection de-homogenization methods by clustering sub-domains of the structure into discrete orientation angles. Pre-computed microstructures for each of the discrete angles are then assembled into each sub-domain. The proposed method is showcased for the design of a simple bumper and hood structure. The material distribution of each component is optimized in a two-dimensional TO problem for maximum stiffness.
Optimization of the Bolted T-Joint of an Electric Bus Body Frame Considering the Fatigue Performance
Authors: Gan Jinlin , Zou Li , Yang Xiujian , Liu Jiaqi
Published: April 2023

This work focuses on the robust optimization of the bolted T-joint part of the steel-aluminum body frame of an electric bus, aiming to improve the performance of fatigue durability of the local structure of the bolted T-joint part. First, finite element model is built for the bolted T-joint part connecting the chassis and the side of the body frame for fatigue durability analysis. Surrogate model for design optimization is fitted by the Kriging method based on the finite element (FE) analysis data. Then, a multi-objective optimization problem is formulated to enhance the fatigue life of the element with the worst fatigue durability performance, and to decrease the deformation of the element with the largest deformation, by choosing the thickness of the beams of the T-joint part as the design variables. A deterministic multi-objective optimization problem is performed by the adaptive simulated annealing (ASA) method. To further improve the reliability of the optimization result, a six-sigma level robust design optimization is carried out based on the Monte Carlo sampling method and the archive-based Micro Genetic Algorithm (AMGA) method. The minimum fatigue times of the optimized bolted T-joint increased by 60.80% compared with that before optimization. The results show that the maximum deformation of the optimized vehicle is reduced by 4.87% and the minimum fatigue times are increased by 25.1% in the common working conditions. The proposed optimization method can effectively improve the comprehensive performance of the bus body frame.
Frequency-Constrained Multi-Material Topology Optimization: Commercial Solver Integrable Sensitivities
Authors: Huang Yuhao , Morris Zane , Sirola Tim , Hardman Andrew , Shi Yifan , Kim Il Yong , Pamwar Manish , Sangha Balbir
Published: April 2023

Numerical tools such as topology optimization (TO) have seen large development in both academic and industrial settings, enabling the optimization of structural objectives and/or attributes, subject to a wide range of constraints, pertinent to the engineering and design problems of automotive and aerospace industries. Classical TO methods assume the use of a single material (SMTO), however, a recent and important advancement in this field is that of multi-material topology optimization (MMTO), capable of simultaneous material existence and selection optimization. This is of heightened importance in the aforementioned industries, where many costly engineering materials can be used, but their selection is delegated to engineer experience. Consideration of modal characteristics (i.e., natural frequencies) in MMTO efforts have seen marginal development in recent years, yet is vital to both industries, who’s products are each subject to uncontrolled environments and vibratory motion. Where frequency has been considered in MMTO, mathematical frameworks require the usage of model attributes that are not extractable from commercial finite element analysis (FEA) solvers, leading to reduced computational efficiency. This paper presents an advancement of the frequency-constrained MMTO sensitivities previously utilized in SMTO, enabling the use of commercial solvers, thus inheriting computational improvements. A derivation of sensitivities, a detailed discussion, and analysis of two case studies have been included, so as to provide the reader with a sound understanding of the nature of the constraint sensitivities, and how they may be able to intuit results.
Multi-Material Topology Optimization Considering Crashworthiness
Authors: Hardman Andrew , Sirola Tim , Huang Yuhao , Morris Zane , Shi Yifan , Kim Il Yong , Pamwar Manish , Sangha Balbir
Published: April 2023

There is an increasing need for lightweight structures in the transportation industry, and within these lightweight structures occupant safety is continually important to all stakeholders. Standard single and multi-material topology optimization (MMTO) techniques are effective for designing lightweight structures subjected to linear objectives and constraints but cannot consider crashworthiness. Crashworthiness must be evaluated using explicit dynamic simulation techniques, as a crash event contains geometric and material nonlinearities which cannot be captured by linear static finite element simulations. Explicit dynamic simulations prevent the calculation of sensitivity derivatives required for conventional gradient-based structural optimization strategies. This paper describes a design tool for multi-material topology optimization considering crashworthiness using the equivalent static load (ESL) method. The ESL method is used to generate linear static sub-problems which replicate the dynamic structural response of explicit dynamic crash simulations in the linear regime. The ESL sub-problems are input to a standard MMTO, optimized results from which are used as input for subsequent crash analyses to update the ESLs for additional sub-problems. The ESLs evolve as the design changes – convergence occurs when the design does not change significantly between subsequent sub-problem optimizations. The objective of this paper is to demonstrate a methodology for an efficient design tool for MMTO considering crashworthiness. Firstly, the ESL and competing methods for crashworthiness optimization are introduced and compared. Next a discussion of the tool’s operation flow as well as the sensitivity equations are presented along with two academic examples demonstrating its implementation. The design tool generates optimized multi-material designs which outperform single-material optimized designs in terms of mass by 7.5% and 17.6% in 2D and 3D models respectively when subjected to crash load cases.
Multi-Objective Bayesian Optimization Supported by Deep Gaussian Processes
Authors: Valladares Homero , Tovar Andres
Published: April 2023

A common scenario in engineering design is the evaluation of expensive black-box functions: simulation codes or physical experiments that require long evaluation times and/or significant resources, which results in lengthy and costly design cycles. In the last years, Bayesian optimization has emerged as an efficient alternative to solve expensive black-box function design problems. Bayesian optimization has two main components: a probabilistic surrogate model of the black-box function and an acquisition functions that drives the design process. Successful Bayesian optimization strategies are characterized by accurate surrogate models and well-balanced acquisition functions. The Gaussian process (GP) regression model is arguably the most popular surrogate model in Bayesian optimization due to its flexibility and mathematical tractability. GP regression models are defined by two elements: the mean and covariance functions. In some modeling scenarios, the prescription of proper mean and covariance functions can be a difficult task, e.g., when modeling non-stationary functions and heteroscedastic noise. Motivated by recent advancements in the deep learning community, this study explores the implementation of deep Gaussian processes (DGPs) as surrogate models for Bayesian optimization in order to build flexible predictive models from simple mean and covariance functions. The proposed methodology employs DGPs as the surrogate models and the Euclidean-based expected improvement as the acquisition function. This approach is compared with a strategy that employs GP regression models. These methodologies solve two analytical problems and one engineering problem: the design of sandwich composite armors for blast mitigation. The analytical problems involve non-convex and segmented Pareto fronts. The engineering problem involves expensive finite element simulations, three design variables, and two expensive black-box function objectives. The results show that the architecture of the DGP model plays an important role in the performance of the optimization approach. If the DGP architecture is adequate, the implementation of DGPs produces satisfactory results; otherwise, the use of GP regression models is preferable.
Vehicle Diagnostics Adapter Cybersecurity Concerns with Wireless Connectivity
Authors: Larson Edward , Ford Wyatt , Lerner Sam , Daily Jeremy
Published: April 2023

Maintaining and diagnosing vehicle systems often involves a technician connecting a service computer to the vehicle diagnostic port through a vehicle diagnostics adapter (VDA). This creates a connection from the service software to the vehicle network through a protocol adapter. Often, the protocols for the personal computer (PC) hosted diagnostic programs use USB, and the diagnostic port provides access to the controller area network (CAN). However, the PC can also communicate to the VDA via WiFi or Bluetooth. There may be scenarios where these wireless interfaces are not appropriate, such as maintaining military vehicles. As such, a method to defeature the wireless capabilities of a typical vehicle diagnostic adapter is demonstrated without access to the source code or modifying the hardware. The process of understanding the vehicle diagnostic adapter system, its hardware components, the firmware for the main processor and subsystems, and the update mechanism is explored. Once the system and binary firmware were understood, a binary patch was created and deployed to the VDA to render the wireless features inoperable while maintaining the existing USB functionality. A series of functional tests were run on the system before and after the patching process, with the results showing that only the targeted wireless functionality was removed and other functions performed as expected. With the ability to patch the VDA demonstrated, the paper concludes by inserting additional features and functions for the VDA, which show how the VDA can be co-opted for offensive cyber operations (for example, manipulating engine hours or vehicle identification number). This exercise confirms the necessity of a more restrictive cybersecurity posture in automotive peripherals with access to critical systems, in particular VDAs, and especially when such peripherals present a wireless interface.
An Intrusion Detection System Based on the Double-Decision-Tree Method for In-Vehicle Network
Authors: Wang Bowen , Zhang Yuance , Zhang Zhaojing , Hu Hongxing , Pu Geguang
Published: April 2023

Intrusion Detection Systems (IDS), technically speaking, is to monitor the network, system, and operation status according to certain security policies, and try to find various attack attempts, attacks or attack results to ensure the confidentiality, integrity and availability of network system resources. Automotive intrusion detection systems can identify and alert by analyzing in-vehicle traffic and log when software applications or devices with malicious activity exist, or the in-vehicle network is tampered and injected. But unfortunately, automotive cybersecurity researchers hardly produce a comprehensive detection method due to the confidential nature of Controller Area Network (CAN) DBC format files, which is a standard long maintained by car manufacturers.

In this paper, an enhanced intrusion detection method is proposed based on the double-decision-tree to classify different attack models for in-vehicle CAN network without the need to obtain complete DBC files. Unlike the existing method that is using data from the simulated CAN traffic traces, we construct three attack models based on real CAN bus traffic collected from Pentium T99. A totally new data split method is provided to divide training set, validation set and test dataset. Three experiments are set to verify this new data split method and the results show that we have achieved high accuracy in the recognition of the three types of attacks, and the model has high operating efficiency.
Cybersecurity in EV’s: Approach for Systematic Secured SW Development through ISO/SAE 21434 & ASPICE
Authors: Ambesange Sandeep , Patwekar Ashwin
Published: April 2023

Cybersecurity (CS) is crucial and significantly important in every product that is connected to the network/internet. At present, society is getting used to a lot of connected devices for multiple day-to-day needs that are as small as controlling the air conditioner (AC) temperature of the house when we are away, to the fully equipped high end modern car which may have 100+ electronic control units (ECU’s) [1]. Hence making it very important to guarantee that every single connected device shall have cybersecurity measures implemented to ensure the safety of the entire system.

Looking into the forecasted worldwide growth in the electric vehicles (EV’s) segment, CS researchers have recently identified several vulnerabilities that exist in EV’s, electric vehicle supply equipment (EVSE) devices, communications to EVs, and upstream services, such as EVSE vendor cloud services, third party systems, and grid operators. The impending impact of attacks on these systems can range from relatively minor local effects to the large-scale national disruptions.

Fortunately, for automotive, there are standards that lay down a strong perspective for the safety and security of road vehicles. ISO/SAE 21434:2021 ensures appropriate consideration of the CS for engineering of electrical & electronic (E/E) systems to keep up with state-of-the-art technology and evolving attack methods. One more such standard is Automotive SPICE (ASPICE) that lays down a process assessment model, when used with a proper assessment methodology helps to identify process related risks. Additional processes have been defined in the process reference and assessment model for the CS engineering in order to incorporate the cybersecurity related processes in the ASPICE scope. This paper aims at providing a model & brief overview to establish a correlation between the ASPICE, ISO/SAE 21434 and the ISO 26262 functional safety (FS) standards for development of a secured cybersecurity software with all the considerations that an organization can undertake.
Vehicle Kinematics-Based Image Augmentation against Motion Blur for Object Detectors
Authors: Zhang Zhuang , Zhang Lijun , Meng Dejian , Huang Luying , Xiao Wei , Tian Wei
Published: April 2023

High-speed vehicles in low illumination environments severely blur the images used in object detectors, which poses a potential threat to object detector-based advanced driver assistance systems (ADAS) and autonomous driving systems. Augmenting the training images for object detectors is an efficient way to mitigate the threat from motion blur. However, little attention has been paid to the motion of the vehicle and the position of objects in the traffic scene, which limits the consistence between the resulting augmented images and traffic scenes. In this paper, we present a vehicle kinematics-based image augmentation algorithm by modeling and analyzing the traffic scenes to generate more realistic augmented images and achieve higher robustness improvement on object detectors against motion blur. Firstly, we propose a traffic scene model considering vehicle motion and the relationship between the vehicle and the object in the traffic scene. Simulations based on typical ADAS test scenes show that the high vehicle speed and near object position is the key factor in generating motion blur. Second, we propose the vehicle-motion-based image augmentation algorithm. The proposed method applies the motion blur on the clear object based on the vehicle's speed and the relative position of the object. Subjective evaluation and multiple objective evaluation indexes including structural similarity index measure (SSIM), perceptual hash, normalized mutual information, and cosine similarity demonstrates that the proposed image augmentation can produce images more consistent with the traffic scenes. Thirdly, we apply the proposed method to the training of object detectors. Experiments on the KITTI dataset as well as real-world driving tests show that the proposed image augmentation achieves a higher robustness improvement than existing image augmentation algorithms on multiple object detectors including CenterNet, YOLOv3, and Faster R-CNN.
Projecting Lane Lines from Proxy High-Definition Maps for Automated Vehicle Perception in Road Occlusion Scenarios
Authors: Carow Kyle , Kadav Parth , Fanas Rojas Johan , Asher Zachary
Published: April 2023

Contemporary ADS and ADAS localization technology utilizes real-time perception sensors such as visible light cameras, radar sensors, and lidar sensors, greatly improving transportation safety in sufficiently clear environmental conditions. However, when lane lines are completely occluded, the reliability of on-board automated perception systems breaks down, and vehicle control must be returned to the human driver. This limits the operational design domain of automated vehicles significantly, as occlusion can be caused by shadows, leaves, or snow, which all occur in many regions. High-definition map data, which contains a high level of detail about road features, is an alternative source of the required lane line information. This study details a novel method where high-definition map data are processed to locate fully occluded lane lines, allowing for automated path planning in scenarios where it would otherwise be impossible. A proxy high-definition map dataset with high-accuracy lane line geospatial positions was generated for routes at both the Eaton Proving Grounds and Campus Drive at Western Michigan University (WMU). Once map data was collected for both routes, the WMU Energy Efficient and Autonomous Vehicles Laboratory research vehicles were used to collect video and high-accuracy GNSS data. The map data and GNSS data were fused together using a sequence of data processing and transformation techniques to provide occluded lane line geometry from the perspective of the ego vehicle camera system. The recovered geometry is then overlaid on the video feed to provide lane lines, even when they are completely occluded and invisible to the camera. This enables the control system to utilize the projected lane lines for path planning, rather than failing due to undetected, occluded lane lines. This initial study shows that utilization of technology outside of the norms of automated vehicle perception successfully expands the operational design domain to include occluded lane lines, a necessary and critical step for the achievement of complete vehicle autonomy.
The Prediction for Adjustable Ability of Electric Vehicle Aggregator Based on Deep-Belief-Network
Authors: Li Bo , Wang Ning , Li Yuan , Huang Yuan
Published: April 2023

In recent years, one of the keys to achieving energy conservation and emission reduction and practicing sustainable development strategies is the wide-area access of large-scale electric vehicles. The charging behavior of large-scale electric vehicles has brought great challenges to the load management and adjustment capacity determination of the power system. Therefore, the prediction of adjustable ability of electric vehicle aggregator based on deep-belief-network is proposed in this paper. First of all, this paper selects the indicators related to the load of the electric bus station: including the arrival time, departure time, and daily mileage of the electric vehicle, from which the SOC variation trend and accurate charging demand of the single electric vehicle are obtained. Secondly, a deep belief network model for load forecasting is established, and the corresponding data set is extracted using historical data, and is used as input together with the load data of electric vehicle aggregators, so as to accurately predict the load situation of electric vehicle aggregators in the next 1 day. Finally, based on the prediction results, the schedulable capacity of the electric vehicle aggregator is obtained. The calculation example shows that the electric vehicle aggregator has a large and stable dispatchable capacity at night. During the day, the user behavior can affect the dispatchable capacity of the aggregator by affecting the state of charge of the electric vehicle. It can be seen that the proposed prediction model has high accuracy and comprehensive consideration.
Techno-Economic Assessment of Utilising Second-Life Batteries in Electric Vehicle Charging Stations
Authors: Salek Farhad , Morrey Denise , Henshall Paul , Resalati Shahaboddin
Published: April 2023

The number of electric vehicles is increasing in line with the global carbon reduction targets. More households are installing electric charging points to complement the existing charging infrastructure. The increasing electricity prices affected by the global energy/economic crisis however pushed more households towards coupling their charging points with renewable energy generation and storage systems to manage the supply and demand of energy more effectively. In this study, an electric charging station equipped with Photovoltaic panels and an electric storage system utilising second-life Electric Vehicles (EV) batteries is designed and analysed. Various electricity generation capacities are considered to be installed on the roof of the case study building ranging from 5m2 and 20m2. The second-life batteries are disposed from EVs with an 80% state of health. MATLAB Simulink is used for mathematical modelling of system. The second-order equivalent circuit model (ECM) is employed for predication of second-life battery parameters, and the model is validated by experimental data using 3h cylindrical NMC cells. The NMC cell degradation data consists of both real and forecast data in this study. The proposed system is designed based on the worst-case scenario with minimum solar radiation in January. The Box-Behnken design of experiment method is also employed to design the case scenarios to perform the parametric study. The results have demonstrated that the maximum peak charge and discharge C-rate values of the battery modules equals to 0.2C and 0.16C, respectively. The optimum design of the charging station is achieved when the solar system covered 53.3% share of the energy consumed by the electric charging station. The second-life battery size and PV area equals to 7.45kWh and 5.15m2, respectively. The optimum total cost of the second-life batteries and PVs based on literature costing data (excluding labour and auxiliary devices costs) is estimated to be around £1371 in this study.