Browse Topic: Computed tomography (CT)
The usage of additively manufactured (AM) notched components for fatigue-critical applications presents non-trivial challenges, such as the ubiquitous presence of volumetric defects in AM parts. Volumetric defects accelerate fatigue crack nucleation, impact short crack growth, and are near-impossible to fully eliminate. This study investigated the synergistic effects of volumetric defects and notch geometry on the fatigue behavior of L-PBF AlSi10Mg and 17-4 PH SS notched specimens. The criticality of the defects on fatigue behavior is investigated using a non-destructive evaluation technique. A classical linear elastic fracture mechanics (LEFM) approach was modified and used to quantify the effects of several factors including notch geometry, defects’ size, and location, on the fatigue crack initiation behavior. The modified LEFM approach utilized X-ray computed tomography data and linear elastic finite element analysis of local stresses in different notch geometries; to calculate and rank the mode-I stress intensity factors of all defects within a notched specimen. The proposed approach was validated by predicting the volumetric defects’ criticalities and confirming them based on fractography.
Ongoing research in simulated vehicle crash environments utilizes postmortem human subjects (PMHS) as the closest approximation to live human response. Lumbar spine injuries are common in vehicle crashes, necessitating accurate assessment methods of lumbar loads. This study evaluates the effectiveness of lumbar intervertebral disc (IVD) pressure sensors in detecting various loading conditions on component PMHS lumbar spines, aiming to develop a reliable insertion method and assess sensor performance under different loading scenarios. The pressure sensor insertion method development involved selecting a suitable sensor, using a customized needle-insertion technique, and precisely placing sensors into the center of lumbar IVDs. Computed tomography (CT) scans were utilized to determine insertion depth and location, ensuring minimal tissue disruption during sensor insertion. Tests were conducted on PMHS lumbar spines using a robotic test system for controlled loading in flexion, compression, and a combination, while monitoring pressure changes. The compression force, flexion angle, and sensor-recorded IVD fluid pressure were recorded during tests. CT images were analyzed to assess sensor placement and its impact on sensing ability. Pressure readings during various loading conditions were examined for different specimens, with data reported from the beginning of tests through relevant loading phases. The study successfully established a methodology for inserting pressure sensors into the IVD and assessed their ability to detect changes in flexion angle, compression, and combined loading. Sensors accurately tracked compression force and detected changes in flexion angle, although with some differences in response. Sensors placed optimally showed expected responses, while those placed suboptimally exhibited variability, particularly in detecting changes during flexion. This variability underscores the importance of sensor placement for accurate detection of loading states. Overall, the study provides a foundation for utilizing pressure sensors to monitor loading states in sled tests, with future work focusing on refining differentiation between loading types.
Magnetic resonance imaging (MRI) and computed tomography (CT) scanning have improved and extended millions of patient lives by giving medical professionals high quality images of injures, tumors, infections, internal bruises, and other areas of concern within patient bodies. While the value of these systems is undeniable, their size, capital cost, and per-use cost limit their availability in certain applications.
With the rapid development of electric vehicles (EVs), lithium-ion batteries (LIBs) with high energy and power density have been widely applied as the power producer of EVs. However, the range of EVs has been criticized. To meet consumer demand for high power and long driving distances, the energy and power density of LIBs are getting higher and higher. However, LIBs with higher energy density are more prone to catastrophic thermal runaway (TR). In recent years, EV accidents due to TR of LIBs have been frequently reported, which makes consumers lose confidence in EVs. To solve the problem, we must understand the mechanism of LIBs TR, thereby reducing the likelihood of TR in EVs. However, the induction mechanism of LIB TR induced by mechanical abuse is sophisticated. This paper focuses on recent advances in the study of thermal TR characteristics of batteries caused by mechanical abuse, including bending, collisions, and penetration. The impact of various mechanical abuses on the TR characteristics of batteries has been summarized. From the onset of mechanical abuse conditions to the occurrences of TR, the interior evolution of the battery is discussed through experiment and theory, to reveal the processes of mechanical deformation and internal short-circuit (ISC) of LIBs. Additionally, an acceleration calorimeter and X-ray computed tomography (CT) are used to investigate the TR process and the evolution of temperature, voltage, and structure of battery components in the battery under mechanical abuse conditions. This paper aims to summarize the latest progress in the study of the mechanism of mechanical abuse-induced battery TR, to help engineers design safe batteries.
In this study, a parametric thoracic spine (T-spine) model was developed to account for morphological variations among the adult population. A total of 84 CT scans were collected, and the subjects were evenly distributed among age groups and both sexes. CT segmentation, landmarking, and mesh morphing were performed to map a template mesh onto the T-spine vertebrae for each sampled subject. Generalized procrustes analysis (GPA), principal component analysis (PCA), and linear regression analysis were then performed to investigate the morphological variations and develop prediction models. A total of 13 statistical models, including 12 T-spine vertebrae and a spinal curvature model, were combined to predict a full T-spine 3D geometry with any combination of age, sex, stature, and body mass index (BMI). A leave-one-out root mean square error (RMSE) analysis was conducted for each node of the mesh predicted by the statistical model for every T-spine vertebra. Most of the RMSEs were less than 2 mm across the 12 vertebral levels, indicating good accuracy. The presented parametric T-spine model can serve as a geometry basis for parametric human modeling or future crash test dummy designs to better assess T-spine injuries accounting for human diversity.
The intent of this document is to define the methodology for suspect parts inspection using radiological inspection. The purpose of radiology for suspect counterfeit part inspection is to detect deliberate misrepresentation of a part, either at the part distributor or original equipment manufacturer (OEM) level. Radiological inspection can also potentially detect unintentional damage to the part resulting from improper removal of part from assemblies, which may include, but not limited to, prolonged elevated temperature exposure during desoldering operations or mechanical stresses during removal. Radiological inspection of electronics includes film radiography and filmless radiography such as digital radiography (DR), real time radiography (RTR), and computed tomography (CT). Radiology is an important tool used in part verification of microelectronic devices. Radiographic analysis is performed on parts to verify that the internal package or die construction is consistent with an exemplar. In case an exemplar is not available, comparisons should be made within a homogenous sample population using the technical data available for that item. If AS6171/5 is invoked in the contract, the base document, AS6171 General Requirements shall also apply.
Lithium-ion batteries now in widespread use for everything from mobile electronics to electric vehicles rely on a liquid electrolyte to carry ions back and forth between electrodes within the battery during charge and discharge cycles. The liquid uniformly coats the electrodes, allowing free movement of the ions.
Automation can produce large quantities of product quickly, but ensuring end-part quality is a critical challenge. Visual, manual, or periodic sampling methodologies can be imprecise, slow, or come in too late to trigger a timely line stoppage once a manufacturing error has occurred, resulting in a high proportion of discarded parts.
In the circuit board industry, an increasing number of parts and boards are proving to be difficult to inspect with automated optical inspection (AOI) because the solder is invisible. Furthermore, high-quality requirements such as bonding strength of the automobile industry and full surface inspection of the solder are increasing. To address these needs, Omron has introduced new technology for accomplishing inspections within the required inline take time (the rate at which a product must be completed to meet customer demand). This has been one of the most challenging requirements for computed tomography (CT) X-ray automatic inspection equipment. For continuous imaging technology, highly accurate positioning control and high-speed image sensing are required.
ABSTRACT
In order to study the influence of lubricant ash on the performance of the CN6 after-treatment system, especially the catalyst characteristics of Coated Gasoline Particulate Filter (CGPF), the system was rapidly aged on the engine bench by blending combustion method, and the ash content of 60g represented the endurance of 200kkm CGPF. The effects of CGPF with different endurance mileage on particulate matter emission, gas light-off temperature and engine performance of a Gasoline Direct Injection (GDI) vehicle were studied on the engine bench, chassis dynamometer and real-road tests. Finally, the ash distribution was analyzed by computed tomography (CT). The results showed that the vehicle equipped with CGPF could meet the requirements of CN6 particulate and gas emission limits under both worldwide harmonized light vehicles test cycle (WLTC) and real driving emission (RDE) tests. With the ash accumulation in the CGPF, the filtration efficiency of CGPF for the particulate number (PN) continuously increased and finally could maintain a high efficiency up to 99.7%. The ash accumulation had a reasonable influence on gas light-off temperature of CGPF (less than 15°C), and had little influence on the maximum conversion efficiency. The increase of ash content in CGPF would increase the CGPF pressure drop and decrease engine torque, which have influenced by about 8.9kPa and 3.5%, but the influence on fuel consumption was not obvious in the external characteristic test. The ash was mainly deposited at the end, especially in the central area of CGPF and the height of 60g ash could reach 41.7mm, which accounted for about 41% of the total length of the carrier. In summary, the after-treatment system can well meet the endurance requirements of 200kkm in CN6 regulation.
The digital twin (DT) refers to a digital replica or virtual model of actual physical product or process that can be applicable for various purposes. In this study, a digital reproduction of the next generation active twist blade, meeting superior durability characteristics and high strength requirements under severe operating environments of a helicopter rotor, is attempted using the up-to-date computed tomography (CT) scheme combined with modern digital image processing technique. The CT scan covers much portion of the blade root, transition, and tip regions where substantial variations in external geometries and/or interior structural layouts are present while limited zones in the airfoil blade region being considered as nonuniform. A three-dimensional (3D) finite element-based DT simulation model is constructed using the high-resolution CT-scan images. The detailed lamination geometries and sequences of layered composites in the blade skin and spar are implemented in the DT model which can be exploited further for durability study or strength analysis. The reconstructed 3D analysis model is used to determine the structural properties of the blade. In parallel, either mechanical or optical measurement methods along with two-dimensional (2D) blade sectional analysis are carried out to cross validate their predictions. Overall, fair to good correlation is obtained between the different set of results. The agreement is good for mass, elastic axis, and flap bending while less satisfactory results are obtained with the torsion rigidity. A sensitivity analysis is also conducted to clarify the impact of modeling cables, nose weight, and manufacturing imperfections on the structural property evaluation of the blade.
This study employed a diesel particulate generator (DPG), with an installed engine oil injector for soot and ash accumulation in a diesel particulate filter (DPF). Ash was generated by engine oil injection into the diesel burner flame. The amount of soot accumulation per loading varied from 0.5 g/L to 8 g/L while ash accumulation amount per loading was maintained at 0.5 g/L. Initially, ash accumulation distribution in the DPF was visualized using X-ray computed tomography (CT). It was revealed that the form of ash accumulation changed depending on the amount of soot accumulation before active regeneration, i.e., a large amount of soot accumulation resulted in plug ash, whereas a small amount of soot accumulation resulted in wall ash. To clarify ash accumulation mechanisms, soot and ash transport behavior in DPF during active regeneration process was directly observed using a high-speed camera through an optically accessible D-shaped cut DPF covered with a quartz glass plate. From the results, it was found that for larger amounts of soot accumulation, the lump of soot in the soot cake layer was transported toward the end plug of the DPF. On the other hand, for smaller amounts of soot accumulation, the lump of soot was not formed in the soot cake layer. Soot was oxidized on the spot and gradually disappeared. In addition, it was found that once the wall ash was formed, the lump of soot could be transported easily, even with a lower amount of soot accumulation.
Catalytic and non-catalytic engine aftertreatment components, such as the diesel oxidation catalyst (DOC), selective catalytic reduction on filter (SCRF), the gasoline particulate filter (GPF) and the diesel particulate filter (DPF) are complex, multifunctional emissions control technologies that are robustly designed for extended use in harsh automotive exhaust environments. Over the useful component lifetime, lubricant-derived inorganic and incombustible ash accumulates in and/or on the surface of the aforementioned aftertreatment components, resulting in degraded performance and other potential problems. In order to better understand effects of ash in such components, a multiscale analytical approach is necessary, requiring a variety of experimental tools. This paper will briefly present a decade of analytical experience at the Sloan Automotive Laboratory at the Massachusetts Institute of Technology and at Kymanetics, Inc., specific to the fundamental understanding of the accumulation of lubricant-derived ash in engine aftertreatment components. Several key experimental tools and techniques will be reviewed including focused ion beam milling (SEM), in-situ X- ray diffraction (XRD), atomic force microscopy (AFM), ultra-high resolution X-ray computed tomography (CT), X-ray fluorescence (XRF), environmental scanning electron microscopy with backscattered electrons (ESEM-BSE), and ultra-small angle X-ray scattering (USAXS), among others.
Metal additive manufacturing (AM) has become increasingly popular to fabricate complex, light-weight, and high- efficiency components for use in the aerospace industry; however, there are inherent limitations in existing AM processes that have delayed widespread implementation for aviation applications. Porosity is just one example of the key characteristics that can impact the mechanical strength of an AM part. This research focuses on a real-time feedback system to detect and correct defects during the powder bed fusion process of aluminum alloys. In this study, AlSi10Mg coupons were built using various AM parameters. The build process was continuously monitored via a high-frequency in-situ infrared camera which had been integrated into a commercial metal powder bed fusion machine. Porosity information (pore location and size) of the as-built AM coupons were characterized using x-ray computed tomography. The monitoring results were post processed and correlated with porosity location, indicating a strong relationship between abnormal sensing signal and pore formation. This demonstrates that the real-time abnormal sensing signal can be a good indicator for identifying pore formation during the AM process. Additionally, Sentient Science Corporation (Sentient) used its advanced modeling technique to simulate the AM build process regarding the melt pool geometry, porosity, and microstructure. Prediction of porosity level at different AM parameters aligned well with the experimental results. Advanced modeling results showed that careful selection of AM settings is required to correct in-process defects. Repair parameters must be tailored to achieve satisfactory correction of individual defects. Combining the in-situ defect monitoring and advanced simulation capabilities enables the creation of a closed-loop feedback control system that provides automatic defect detection and correction action in powder bed additive manufacturing process.
Crash safety researchers have an increased concern regarding the decreased thoracic deflection and the contributing injury causation factors among the elderly population. Sternum fractures are categorized as moderate severity injuries, but can have long term effects depending on the fragility and frailty of the occupant. Current research has provided detail on rib morphology, but very little information on sternum morphology, sternum fracture locations, and mechanisms of injury. The objective of this study is two-fold (1) quantify sternum morphology and (2) document sternum fracture locations using computed tomography (CT) scans and crash data. Thoracic CT scans from the University of Michigan Hospital database were used to measure thoracic depth, manubriosternal joint, sternum thickness and bone density. The sternum fracture locations and descriptions were extracted from 63 International Center for Automotive Medicine (ICAM) crash cases, of which 22 cases had corresponding CT scans. The University of Michigan Internal Review Board (HUM00043599 and HUM00041441) approved the use of crash cases and CT scan data. The sternum morphomics data showed the thoracic depth increased, except for the 60-74-year-old age group. The average sternum thickness was greater in the older age groups. The sternum bone density decreased from youngest to oldest age groups. The angle between the manubrium and the sternum body decreased by 5.6° between the youngest and oldest age groups. The frequency of sternum fractures increased after age 45. Fractures were most frequent in the sternum body. The seat belt webbing was coded as the source of 54% of the sternum fractures.
In recent years along with stringent the regulations, vehicles equipped with gasoline particulate filter (GPF) have started to launch. Compared to bare GPF, coated GPF (cGPF) requires not only PN filtration efficiency, low pressure drop, but also purification performance. In the wall flow type cGPF having a complicated the pore shape, the pore structure further irregularly changes depending on the coated state of the catalyst, so it is difficult to understand the matter of in-wall. In order to advance of cGPF function, it was researched that revealing the relevance between pore structure change in the wall and GPF function. Therefore, to understand the catalyst coated state difference, cGPF of several coating methods were prepared, and their properties were evaluated by various analyses, and performance was tested. First of all, as a result of Mercury porosimetry analysis revealed that the pore diameter of the filter wall of GPF is a key factor for the pressure drop and the Particulate Number filtration efficiency. Next, as a result of analyzing the 3D model created by the μX-ray computed tomography image, it was found that the uniformity of the catalyst coat is a key factor for the purification performance. On the other hand, from images showing catalyst coated state of cGPF using electron probe micro analyzer, it was possible to quantify and evaluated uniform of catalyst coated state, by 2D digital image analysis. From the above those studies, cGPF could become to be designed with the best balance of low pressure drop, high purification performance and high PN filtration efficiency.
Recent legislation enacted for the European Union (EU) and the United States calls for a substantial reduction in particulate mass (and number in the EU) emissions from gasoline spark-ignited vehicles. The most prominent technology being evaluated to reduce particulate emissions from a gasoline vehicle is a wall flow filter known as a gasoline particulate filter (GPF). Similar in nature to a diesel particulate filter (DPF), the GPF will trap and store particulate emissions from the engine, and oxidize said particulate with frequent regeneration events. The GPF will also collect ash particles in the wall flow substrate, which are metallic components that cannot be oxidized into gaseous components. Due to high temperature operation and frequent regeneration of the GPF, the impact of ash on the GPF has the potential to be substantially different from the impact of ash on the DPF. Therefore, traditional accelerated ash loading methods used for DPFs may not be applicable to the GPF technology. This paper summarizes three accelerated ash loading strategies that were evaluated and compared to a field generated component to understand the applicability of the accelerated methods. CT Scan imaging was used to compare each ash loading technique relative to a field generated GPF.
Voids and ply waviness are the most common types of fabrication process induced defects in composite structures that can have detrimental effects on their load bearing capacity. To date, extensive works have been done on the characterization of fabrication induced defects on the mechanical properties of composites but less study has been performed to determine the effects of defects on the failure progression. Given the durability and damage tolerance requirements for certification and design of composite structures, it is important to evaluate the effects of these defects on the damage initiation and failure progression of a loaded composite structure. In this study, void and ply waviness information are extracted from X-ray computed tomography (CT) and optical microscopy and an efficient image-to-numerical solution is developed to map the detected voids and ply waviness into a finite element based progressive failure analysis model. An interlaminar tensile (ILT) test specimen under four point bending is used to demonstrate the capability of our response and progressive damage prediction.
Composite helicopter rotor components are typically thick and often have areas with a tight radius of curvature, which make them especially prone to process-induced defects, including wrinkles and voids at ply interfaces. Such flaws cause high rejection rates in production of flight-critical components and structure. This work seeks to fill the gaps in understanding generation of the noted defects in contoured polymer-matrix composite (PMC) laminates. In particular, understanding and modelling defect formation at the early stages of the manufacturing process might be the missing link to enable the development of practical engineering solutions allowing for better control of the manufacturing process of contoured composite parts. In this work, an approach based on a continuum description of the uncured prepreg material, including the initial bulk or void content, and finite element modelling (FEM) is used to simulate the consolidation process at the early stages of manufacturing of contoured laminates. The simulation predicts instabilities leading to formation of both wrinkles and voids at ply interfaces during laminate debulking or vacuum consolidation. Applicability of the method to consolidation in both closed-cavity and open-face tooling is also demonstrated. FEM results show good correlation with X-ray Computed Tomography data. This work also introduces a new simulation concept based on finite element and discrete modelling of voids at ply interfaces to improve accuracy of predicting their evolution during the debulking operations.
The purpose of this study was to use detailed medical information to evaluate thoracic injuries in elderly patients in real world frontal crashes. In this study, we used analytic morphomics to predict the effect of torso geometry on rib fracture, a major source of injury for the elderly. Analytic morphomics extracts body features from computed tomography (CT) scans of patients in a semi-automated fashion. Thoracic injuries were examined in front row occupants involved in frontal crashes from the International Center for Automotive Medicine (ICAM) database. Among these occupants, two age groups (age < 60 yr. [Nonelderly] and age ≥ 60 yr. [Elderly]) who suffered severe thoracic injury were analyzed. Regression analyses were conducted to investigate injury outcomes using variables for vehicle, demographics, and morphomics. Compared to the nonelderly group, the elderly group sustained more rib fractures. Logistic regression models were fitted with different configurations of variables predictive of the Maximum Abbreviated Injury Scale of the thoracic region (MAISthx 3+). The performance of models was assessed using area under the receiver operating characteristic curve (AUC). AUC is a widely-used “rating” method to describe the accuracy of prediction models. It represents the probability that a randomly chosen positive subject with higher predicted risk than a randomly chosen negative subject. An area of 1 represents a perfect model; an area of 0.5 represents a worthless model. The model developed based solely on vehicle data had an AUC of 0.58. When demographic data was combined with vehicle data, the model prediction improved to an AUC of 0.66. The AUC associated with vehicle and morphomics data increased to 0.72 and increased again to 0.79 when combining vehicle, demographic, and morphomics variables. The important morphomics variables were the rib’s in-plane shape, rib angle, and spine-to-back skin, which represents fat thickness in the posterior trunk. Morphomics variables such as skeletal geometry and fat distribution can be precisely adjusted in a finite element human body model or anthropomorphic testing device to represent occupants of different body shapes and sizes and are thus more valuable in assessing injury during vehicle crashes.
Staying competitive calls for medical equipment OEMs to constantly keep pace with the speed of innovation. Better medical treatment and care can be achieved with fast, accurate results from advanced imaging applications such as CT scanning and MRI that process and analyze large amounts of data, requiring developers to build devices that deliver ever-increasing computing performance. Supporting this demand, high-performance embedded computing platforms that use the latest faster and more efficient processors are essential in helping OEMs keep up with these enhanced performance requirements.
Surgeons can swab a patient’s exposed liver lightly on the surface with a special stylus, capturing the shape of the organ during surgery, and a computer can match that image with the CT scan on a screen. This GPS-like ability is far better than guessing where the tumor and vessels are by feeling for them, but even this road map can be off by centimeters and leaves surgeons guessing.
The salient features of modern gasoline direct injection include cavitation, flash boiling, and plume/plume interaction, depending on the operating conditions. These complex phenomena make the prediction of the spray behavior particularly difficult. The present investigation combines mass-based experimental diagnostics with an advanced, in-house modeling capability in order to provide a multi-faceted study of the Engine Combustion Network’s Spray G injector. First, x-ray tomography is used to distinguish the actual injector geometry from the nominal geometry used in past works. The actual geometry is used as the basis of multidimensional CFD simulations which are compared to x-ray radiography measurements for validation under cold conditions. The influence of nozzle diameter and corner radius are of particular interest. Next, the model is used to simulate flash-boiling conditions, in order to understand how the cold flow behavior corresponds to flashing performance.
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