Geometrical Locating Scheme for Complex Hybrid Manufacturing: Multiple Additive Manufacturing and Machining

The technology of additive manufacturing is rapidly developing as one of the most sustainable alternatives for the traditional manufacturing processes. Additive manufacturing technologies offer numerous advantages such as weight reduction, design freedom, reducing material waste and so on. But to manufacture complex components, the traditional manufacturing processes are still needed to obtain the final desired geometry. DiSAM is one such project that is happening in Sweden, aiming to improve the technology readiness of additive manufacturing processes. A complex aircraft component is being manufactured in this project using both additive manufacturing and traditional manufacturing processes. In this process of complex manufacturing where, multiple additive manufacturing processes and machining processes are involved, the effect of the locating scheme in each step of manufacturing process plays a vital role in providing the desired geometrical accuracy. This thesis work was carried out to develop a locating scheme that was most suitable to follow in this complex manufacturing process chain. The component from the engine exit structure of a gas turbine engine which is termed as "H-Sector" was the product in focus. Information was collected through interviews with the stakeholders of the DiSAM project. The manufacturing process flow was studied to finalize on the parameters that affects the geometrical accuracy at different manufacturing steps. The critical areas of the components were identified which needs to be focused in developing locating scheme at each manufacturing step. The software RD&T was used in evaluating the locating schemes. Different locating scheme strategies were developed. Sensitivity analysis was carried out to compare between the strategies and finalizing on the final locating scheme. This thesis outcome will help in making decisions regarding the locating scheme for the DiSAM project. The same method can be followed in developing different locating scheme for different geometry in the future

A fuzzy-PID controller in shell and tube heat exchanger simulation modeled for temperature control

Shell and tube heat exchanger is the most generally utilized types of heat exchanger for heat transfer in many industrial purposes. Shell and tube heat exchanger comprises a set of unit. One unit includes mechanical parts and another unit consists of controlling part. Both the unit has to be modelled to ensure the efficient operation of shell and tube heat exchanger. The mechanical modelling is completely established on the type of applications. The controller modelling is independent of the kind of applications. The controller only needs the input fluid and output fluid properties such as temperature and flow rate.  Hence the primary objective of the paper is to focus on the controller part for enhancing the heat exchanger performance. This paper proposes the novel fuzzy-PID controlling technique based on the multiplication operation to make the settling time and overshoot of setpoint temperature to be less to a greater extent and the results are compared with the conventional PI method with various tuning algorithms

Early results on the use of biomaterials as adjuvant to abdominal wall closure following cytoreduction and hyperthermic intraperitoneal chemotherapy

<p>Abstract</p> <p>Background</p> <p>Hyperthermic chemotherapy applies thermal energy to both abdominal wall as well as the intra-abdominal viscera. The combination of the hyperthemia, chemotherapy and cytoreductive surgery (CRS) is associated with a defined risk of abdominal wall and intestinal morbidity reported to be as high as 15%, respectively to date, no studies have evaluated the use of biomaterial mesh as adjuvant to abdominal wall closure in this group of patients. In the present report, we hypothesized that post HIPEC closure with a biomaterial can reduce abdominal wall morbidity after CRS and hyperthermic intraperitoneal chemotherapy.</p> <p>Materials and methods</p> <p>All patients treated with HIPEC in a tertiary care center over 12 months (2008-2009) period were included. Eight patients received cytoreductive surgery followed by HIPEC for 90 minutes using Mitomycin C (15 mg q 45 minutes × 2). Abdominal wall closure was performed using Surgisis (Cook Biotech.) mesh in an underlay position with 3 cm fascial overlap-closure. Operative time, hospital length of stay (LOS) as well as postoperative outcome with special attention to abdominal wall and bowel morbidity were assessed.</p> <p>Results</p> <p>Eight patients, mean age 59.7 ys (36-80) were treated according to the above protocol. The primary pathology was appendiceal mucinous adenocarcinoma (n = 3) colorectal cancer (n = 3), and ovarian cancer (n = 2). Four patients (50%) presented initially with abdominal wall morbidity including incisional ventral hernia (n = 3) and excessive abdominal wall metastatic implants (n = 1). The mean peritoneal cancer index (PCI) was 8.75. Twenty eight CRS were performed (3.5 CRS/patient). The mean operating time was 6 hours. Seven patients had no abdominal wall or bowel morbidity, the mean LOS for these patients was 8 days. During the follow up period (mean 6.3 months), one patient required exploratory laparotomy 2 weeks after surgery and subsequently developed an incisional hernia and enterocutaneous fistula.</p> <p>Conclusion</p> <p>The use of biomaterial mesh in concert with HIPEC enables the repair of concomitant abdominal wall hernia and facilitates abdominal wall closure following the liberal resection of abdominal wall tumors. Biomaterial mesh prevents evisceration on repeat laparotomy and resists infection in immunocompromised patients even when associated with bowel resection.</p

Model predictive control of connected spacecraft formation.

In this contribution the authors discuss the application of Model Predictive Control (MPC) to achieve a connected network formation of spacecrafts. A set of three spacecrafts are used to achieve in-plane formation which are initially in a connected network. Two scenarios including formation control and formation control with collision avoidance in a leader-follower configuration is addressed through simulation studies. The aspect of MPC stability and network connectivity is also addressed briefly in the context of formation control

Underwater localization using SAR satellite data.

This study delves into the realm of Underwater Wireless Sensor Networks (UWSN) and explores contemporary methods of ocean exploration. It provides an extensive background on UWSN, detailing existing approaches to underwater localization. The study then introduces a novel contribution to this domain by leveraging advanced satellite technology. Employing a pre-trained deep learning model from ArcGIS, static ships within the study area are identified using C-band Synthetic Aperture Radar (SAR) satellite imagery. The identified ship locations serve as reference nodes for underwater localization. Utilizing range-based multilateration in the UnetStack environment, the study achieves precise localization of underwater nodes. The proposed approach demonstrates an error of less than 1% when compared to the actual positions of the underwater nodes, showcasing its effectiveness in enhancing the field of underwater exploration and localization

Solar-powered ROV: advancing underwater exploration with renewable energy.

Considering the importance of remotely operated vehicles (ROVs) in conducting inspections, data collection, and exploration beneath the sea surface, this paper proposes a solar-powered ROV solution. Solar power is employed to power the ROV/AUV, with an appropriately designed solar panel providing 5 hours of performance for the Blue ROV. A miniaturized 10Hp/12kg ROV is being considered for underwater activities, with an energy demand load of 943.68W. To meet this demand, solar panels are installed on floating platforms to generate the necessary power, with meticulous calculations determining the best number and size of solar modules. In order to ensure continuous operation, inverters, charge controllers, and battery banks are sized accordingly. The proposed model optimizes silicon solar cells using the COMSOL Multiphysics environment. Simulations in COMSOL Multiphysics validate results against design parameters, confirming adherence to calculated values. The use of solar-powered systems improves operational effectiveness while also ensuring long-term sustainability in maritime activities. The solar-powered ROV represents a significant step towards environmentally conscious and efficient underwater exploration in the Gulf of Guinea and elsewhere by utilizing renewable energy

An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers

Tracking and estimation of surgical tool pose based on the vision system for surgical robot.

The aim of this research is to customise a surgical robot. This research presents a Virtual Dynamic Tri-crossbar and a Virtual Stable Graph (VDT-VSG) which simplifies the task of tracing the needle angle and location

Implementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems.

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined with a low-computational load while being on-line adaptable to changes in the control scenario. Examples for such scenarios are cooperative control, task-based control and fault-tolerant control, where the system's topology, dynamics, objectives and constraints are changing. The framework combines a fast Nonlinear Model Predictive Control (NMPC), a communication interface with the Robot Operating System (ROS) as well as a modularization that allows an event-based change of the NMPC scenario. To experimentally validate performance and event-based adaptability of the framework, this paper is using a cooperative control scenario of Unmanned Aerial Vehicles (UAVs)