Flexible Aerodynamic Part Feeding Using High-Speed Image Processing

In modern assembly systems, manufacturers expect a high level of flexibility and efficiency. As an interface between internal logistics and the actual assembly, part feeding technology plays a decisive role in the manufacturing process. Therefore, in this work, we propose a new way of flexible part feeding based on image processing and the proven principle of aerodynamic feeding technology. With a high-speed camera, we analyze the workpiece’s movement during the orientation process and automatically adjust the system parameters to ensure reliable and efficient feeding. Based on three parameters of the workpiece’s trajectory, we develop an algorithm that can systematically find suitable parameter combinations for efficient and reliable feeding. With the proposed concept, retooling for new workpieces can be achieved quickly, using only few components for the parameter setting. At the same time, no hardware changes are required for retooling when handling new components

Unmet needs in pneumonia research: a comprehensive approach by the CAPNETZ study group

INTRODUCTION: Despite improvements in medical science and public health, mortality of community-acquired pneumonia (CAP) has barely changed throughout the last 15 years. The current SARS-CoV-2 pandemic has once again highlighted the central importance of acute respiratory infections to human health. The “network of excellence on Community Acquired Pneumonia” (CAPNETZ) hosts the most comprehensive CAP database worldwide including more than 12,000 patients. CAPNETZ connects physicians, microbiologists, virologists, epidemiologists, and computer scientists throughout Europe. Our aim was to summarize the current situation in CAP research and identify the most pressing unmet needs in CAP research. METHODS: To identify areas of future CAP research, CAPNETZ followed a multiple-step procedure. First, research members of CAPNETZ were individually asked to identify unmet needs. Second, the top 100 experts in the field of CAP research were asked for their insights about the unmet needs in CAP (Delphi approach). Third, internal and external experts discussed unmet needs in CAP at a scientific retreat. RESULTS: Eleven topics for future CAP research were identified: detection of causative pathogens, next generation sequencing for antimicrobial treatment guidance, imaging diagnostics, biomarkers, risk stratification, antiviral and antibiotic treatment, adjunctive therapy, vaccines and prevention, systemic and local immune response, comorbidities, and long-term cardio-vascular complications. CONCLUSION: Pneumonia is a complex disease where the interplay between pathogens, immune system and comorbidities not only impose an immediate risk of mortality but also affect the patients’ risk of developing comorbidities as well as mortality for up to a decade after pneumonia has resolved. Our review of unmet needs in CAP research has shown that there are still major shortcomings in our knowledge of CAP

Geomechanical/ Geochemical Modeling Studies onducted Within the International DECOVALEX Project

The DECOVALEX project is an international cooperative project initiated by SKI, the Swedish Nuclear Power Inspectorate, with participation of about 10 international organizations. The general goal of this project is to encourage multidisciplinary interactive and cooperative research on modeling coupled thermo-hydro-mechanical-chemical (THMC) processes in geologic formations in support of the performance assessment for underground storage of radioactive waste. One of the research tasks, initiated in 2004 by the U.S. Department of Energy (DOE), addresses the long-term impact of geomechanical and geochemical processes on the flow conditions near waste emplacement tunnels. Within this task, four international research teams conduct predictive analysis of the coupled processes in two generic repositories, using multiple approaches and different computer codes. Below, we give an overview of the research task and report its current status

Results From an International Simulation Study on Couples Thermal, Hydrological, and Mechanical (THM) Processes Near Geological Nuclear Waste Repositories

As part of the ongoing international DECOVALEX project, four research teams used five different models to simulate coupled thermal, hydrological, and mechanical (THM) processes near waste emplacement drifts of geological nuclear waste repositories. The simulations were conducted for two generic repository types, one with open and the other with back-filled repository drifts, under higher and lower postclosure temperatures, respectively. In the completed first model inception phase of the project, a good agreement was achieved between the research teams in calculating THM responses for both repository types, although some disagreement in hydrological responses is currently being resolved. In particular, good agreement in the basic thermal-mechanical responses was achieved for both repository types, even though some teams used relatively simplified thermal-elastic heat-conduction models that neglected complex near-field thermal-hydrological processes. The good agreement between the complex and simplified process models indicates that the basic thermal-mechanical responses can be predicted with a relatively high confidence level

Numerical error in groundwater flow and solute transport simulation

Models of groundwater flow and solute transport may be affected by numerical error, leading to quantitative and qualitative changes in behavior. In this paper we compare and combine three methods of assessing the extent of numerical error: grid refinement, mathematical analysis, and benchmark test problems. In particular, we assess the popular solute transport code SUTRA [ Voss, 1984 ] as being a typical finite element code. Our numerical analysis suggests that SUTRA incorporates a numerical dispersion error and that its mass-lumped numerical scheme increases the numerical error. This is confirmed using a Gaussian test problem. A modified SUTRA code, in which the numerical dispersion is calculated and subtracted, produces better results. The much more challenging Elder problem [ Elder, 1967 ; Voss and Souza, 1987 ] is then considered. Calculation of its numerical dispersion coefficients and numerical stability show that the Elder problem is prone to error. We confirm that Elder problem results are extremely sensitive to the simulation method used.Juliette A. Woods, Michael D. Teubner, Craig T. Simmons and Kumar A. Naraya

Complementary hydro-mechanical coupled finite/discrete element and microseismic modelling to predict hydraulic fracture propagation in tight shale reservoirs

This paper presents a novel approach to predict the propagation of hydraulic fractures in tight shale reservoirs. Many hydraulic fracture modelling schemes assume that the fracture direction is pre-seeded in the problem domain discretization. This is a severe limitation as the reservoir often contains large numbers of pre-existing fractures that strongly influence the direction of the propagating fracture. To circumvent these shortcomings a new fracture modelling treatment is proposed where the introduction of discrete fracture surfaces is based on new and dynamically updated geometrical entities rather than the topology of the underlying spatial discretization. Hydraulic fracturing is an inherently coupled engineering problem with interactions between fluid flow and fracturing when the stress state of the reservoir rock attains a failure criterion. This work follows a staggered hydro-mechanical coupled finite/discrete element approach to capture the key interplay between fluid pressure and fracture growth. In field practice the fracture growth is hidden from the design engineer and microseismicity is often used to infer hydraulic fracture lengths and directions. Microsesimic output can also be computed from changes of the effective stress in the geomechanical model and compared against field microseismicity. A number of hydraulic fracture numerical examples are presented to illustrate the new technology

Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges

In recent decades, we have witnessed great advances on the Internet of Things, mobile devices, sensor-based systems, and resulting big data infrastructures, which have gradually, yet fundamentally influenced the way people interact with and in the digital and physical world. Many human activities now not only operate in geographical (physical) space but also in cyberspace. Such changes have triggered a paradigm shift in geographic information science (GIScience), as cyberspace brings new perspectives for the roles played by spatial and temporal dimensions, e.g., the dilemma of placelessness and possible timelessness. As a discipline at the brink of even bigger changes made possible by machine learning and artificial intelligence, this paper highlights the challenges and opportunities associated with geographical space in relation to cyberspace, with a particular focus on data analytics and visualization, including extended AI capabilities and virtual reality representations. Consequently, we encourage the creation of synergies between the processing and analysis of geographical and cyber data to improve sustainability and solve complex problems with geospatial applications and other digital advancements in urban and environmental sciences