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In this paper, I applaud but also critique the project to integrate the literatures on stakeholders, non-market strategy, and social movements under the umbrella of business and society. My main concern is that some may perceive this integrative effort as hinging on a kind of applied economic imagery of actors and interests that valorizes instrumental, strategic action. Building on scholarship at the interface of social movements and organizations, I argue for the fruitfulness of a broader institutional approach to business and society.

In organizations that have to meet demands from multiple sponsors, and that mix missions from different spheres, such as “civic,” “market,” “family,” how do participants orient themselves, so they can interact appropriately? Do participants’ practical navigation techniques have unintended consequences? To address these two questions, the authors draw on an ethnography of US youth programs whose sponsors required multiple, conflicting logics, speed, and precise documentation. The authors develop a concept, navigation techniques: participants’ shared unspoken methods of orienting themselves and appearing to meet demands from multiple logics, in institutionally complex projects that require frequent documentation. These techniques’ often have unintended consequences.

High resolution simulations of body-internal electric field strengths induced by magneto-quasistatic fields from wireless power transfer systems are computationally expensive. The exposure simulation can be split into two separate simulation steps allowing the calculation of the magnetic flux density distribution, which serves as input into the second simulation step to calculate the body-internal electric fields. In this work, the magnetic flux density is interpolated from in situ measurements in combination with the scalar-potential finite difference scheme to calculate the resulting body-internal field. These calculations are supposed to take less than 5 s to achieve a near real-time visualization of these fields on mobile devices. The purpose of this work is to present an implementation of the simulation on graphics processing units (GPUs), allowing for the calculation of the body-internal field strength in about 3 s.

This work uses the co-simulation scalar-potential finite difference scheme to determine the body-internal electric field strength of human models with a voxel resolution of 2 × 2 × 2 mm³. The scheme is implemented on GPUs. This simulation scheme requires the magnetic flux density distribution as input, determined from radial basis functions.

Using NVIDIA A100 GPUs, the body-internal electric field strength with high-resolution models and 8.9 million degrees of freedom can be determined in about 2.3 s.

This paper describes in detail the used scheme and its implementation to make use of the computational performance of modern GPUs.

This paper aims to present a fast and modular framework implementation for the thermal analyses of foreign metal objects in the context of wireless power transfer (WPT) to evaluate whether they pose a hazard to the system. This framework serves as a decision-making tool for determining the necessity of foreign object detection in certain applications and at certain transmitted power levels.

To assess the necessity of implementing foreign object detection, the considered WPT system is modeled, and Arnoldi-Krylov-based model order reduction is applied to generate separate reduced models of the ground and vehicle modules of the WPT system. This enables interoperable evaluations to be conducted. Further discussion on the implementation details of the system-level simulations used to evaluate the electrical and thermal characteristics is provided. The resulting modular implementation allows for efficient evaluation of the thermal behavior of the wireless charging system at various transferred power levels and under various boundary conditions.

Based on the transferred power level, the WPT model, the relative positioning between the vehicle and the charging pad and the charging time, it may be necessary to divide the area of the charging pad into multiple regions for the purpose of implementing foreign object detection.

While the tools and fundamentals of thermal analysis are widely known and used, their application to high-power WPT systems for electric vehicles has not yet been thoroughly discussed in this form in the literature. The approach presented in this paper is not limited to the specific WPT model discussed but rather is directly applicable to other WPT models as well.

Magneto-quasi-static fields emanated by inductive charging systems can be potentially harmful to the human body. Recent projects, such as TALAKO and MILAS, use the technique of wireless power transfer (WPT) to charge batteries of electrically powered vehicles. To ensure the safety of passengers, the exposing magnetic flux density needs to be measured in situ and compared to reference limit values. However, in the design phase of these systems, numerical simulations of the emanated magnetic flux density are inevitable. This study aims to present a tool along with a workflow, based on the Scaled-Frequency Finite Difference Time-Domain and Co-Simulation Scalar Potential Finite Difference schemes, to determine body-internal magnetic flux densities, electric field strengths and induced voltages into cardiac pacemakers. The simulations should be time efficient, with lower computational costs and minimal human workload.

The numerical assessment of the human exposure to magneto-quasi-static fields is computationally expensive, especially when considering high-resolution discretization models of vehicles and WPT systems. Incorporating human body models into the simulation further enhances the number of mesh cells by multiple millions. Hence, the number of simulations including all components and human models needs to be limited while efficient numerical schemes need to be applied.

This work presents and compares four exposure scenarios using the presented numerical methods. By efficiently combining numerical methods, the simulation time can be reduced by a factor of 3.5 and the required storage space by almost a factor of 4.

This work presents and discusses an efficient way to determine the exposure of human beings in the vicinity of wireless power transfer systems that saves computer simulation resources and human workload.

Inductive charging systems for electrically powered cars produce a magneto-quasistatic field and organism in the vicinity might be exposed to that field. Magneto-quasistatic fields induce electric fields in the human body that should not exceed limits given by the International Commission of Non-Ionizing Radiation protection (ICNIRP) to ensure that no harm is done to the human body. As these electric fields cannot be measured directly, they need to be derived from the measured magnetic flux densities. To get an almost real-time estimation of the harmfulness of the magnetic flux density to the human body, the electric field needs to be calculated within a minimal computing time. The purpose of this study is to identify fast linear equations solver for the discrete Poisson system of the Co-Simulation Scalar Potential Finite Difference scheme on different graphics processing unit systems.

The determination of the exposure requires a fast linear equations solver for the discrete Poisson system of the Co-Simulation Scalar Potential Finite Difference (Co-Sim. SPFD) scheme. Here, the use of the AmgX library on NVIDIA GPUs is presented for this task.

Using the AmgX library enables solving the equation system resulting from an ICNIRP recommended human voxel model resolution of 2 mm in less than 0.5 s on a single NVIDIA Tesla V100 GPU.

This work is one essential advancement to determine the exposure of humans from wireless charging system in near real-time from in situ magnetic flux density measurements.

The simulation of magnetic fields with geometric discretization schemes using magnetic vector potentials involves the solution of very large discrete consistently singular curl‐curl systems of equations. Geometric and algebraic multigrid schemes for their solution require intergrid transfer operators of restriction and prolongation that achieve the discrete conservation of integral quantities serving as state‐variables of geometric discretization methods. For non‐conservative restriction operations, a consistency error correction operator related to an algebraic filtering is proposed. Numerical results show the effects of the consistency correction for a non‐nested geometric multigrid method.

A combination of both time step adaptivity and spatial mesh adaptivity is presented for transient magneto‐quasistatic fields.

Error controlled time step adaptivity is achieved using an implicit integration scheme and the spatial mesh resolution is adapted in each time step in order to effectively resolve the appearing and disappearing local transient saturation effects and eddy current layers. Two spatial refinement strategies are considered, the red‐green refinement leading to a regular mesh and the red refinement leading to an irregular mesh. Numerical results for 2d nonlinear magneto‐dynamic problems are presented.

An algorithm is proposed which computes the solution of a transient magnetostatic problem given a user prescribed error tolerance for the time stepping and the spatial refinement. The red refinement leading to irregular meshes requires projection techniques in the iterative conjugate gradient solver. However, the algorithm with red‐green refinement turns out to perform faster since the projection is too expensive.

The combination of error controlled time stepping and spatial adaptivity is firstly established in electromagnetic field computation.

This paper traces how in Britain and Germany, for-profit and non-profit businesses coevolved with political-economic institutions. Starting in the late eighteenth century, Britain embraced the logic of liberal capitalism, although the path was not smooth. Over the same period, German states balanced both liberal and social-welfare ideals. Social-welfare ideals did not gain support in Britain until the start the twentieth century. The market logic embodied by for-profit businesses was more congruent with liberal capitalism than with social-welfare capitalism, so business corporations thrived more in Britain than in Germany. Yet in both countries, the growing number and power of for-profit businesses created problems for farmers, workers, and small producers. They sought to solve their problems by launching non-profit businesses – co-operatives, mutual-aid societies, and credit co-operatives – combining the ideals of community, enterprise, and self-help. British non-profits gained support from authorities by emphasizing their self-help and enterprise ideals, which were congruent with liberal capitalism, over the community idea, which was not. In contrast, German non-profits gained support by emphasizing all three ideals, as two were congruent with liberal capitalism and all three with social-welfare capitalism. Our analysis reveals how the success of different forms of business, embodying different institutional logics, depends on prevailing political-economic logics. It also shows how the existence and technical success of various organizational forms shapes elites’ perceptions and through them, societal-level logics of capitalism.

In this chapter, the author argues that Austrians are perhaps uniquely placed to be effective practitioners of causal inference techniques on observational data. This is because, while the methods are easy to implement, their validity and value lies in a detailed, “analytical/historical” narrative to accompany the findings. This is true for several reasons. (1) all the models have identifying assumptions (e.g., no spillovers and parallel trends) that are best addressed by an exposition of the institutional/economic/historical milieu in place before and after the treatment under study; (2) determination of external validity also requires detailed institutional and historical knowledge; and (3) researchers often want to know the mechanisms producing the reduced form result that comes out of most causal inference studies. Here again, institutional and historical learning is crucial. My conclusion is that Austrians should add the tools of causal inference with observational data to their arsenal of analysis. This would be good both for their publication prospects and for the profession at large.