Research Computing and Data (RCD) professionals play a crucial role in supporting and advancing research that involve data and/or computing, however, there is a critical shortage of RCD workforce, and organizations face challenges in recruiting and retaining RCD professional staff. It is not obvious to people outside of RCD how their skills and experience map to the RCD profession, and staff currently in RCD roles lack resources to create a professional development plan. To address these gaps, the CaRCC RCD Career Arcs working group has embarked upon an effort to gain a deeper understanding of the paths that RCD professionals follow across their careers. An important step in that effort is a recent survey the working group conducted of RCD professionals on key factors that influence decisions in the course of their careers. This survey gathered responses from over 200 respondents at institutions across the United States. This paper presents our initial findings and analyses of the data gathered. We describe how various genders, career stages, and types of RCD roles impact the ranking of these factors, and note that while there are differences across these groups, respondents were broadly consistent in their assessment of the importance of these factors. In some cases, the responses clearly distinguish RCD professionals from the broader workforce, and even other Information Technology professionals.

Jennifer M. Rieser,1,* Perrin E. Schiebel,1 Arman Pazouki,2 Feifei Qian,3,† Zachary Goddard,4 Kurt Wiesenfeld,1 Andrew Zangwill,1 Dan Negrut,5 and Daniel I. Goldman1,‡ 1School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA 2Department of Mechanical Engineering, California State University, Los Angeles, CA 90032, USA 3School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA 4School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA 5Department of Mechanical Engineering, University of Wisconsin—Madison, Madison, WI 53706, USA

Natural and artificial self-propelled systems must manage environmental interactions during movement. Such interactions, which we refer to as active collisions, are fundamentally different from momentum-conserving interactions studied in classical physics, largely because the internal driving of the locomotor can lead to persistent contact with heterogeneities. Here, we experimentally and numerically study the effects of active collisions on a laterally-undulating sensory-deprived robophysical model, whose dynamics are applicable to self-propelled systems across length scales and environments. The robot moves via spatial undulation of body segments, with a nearly-linear center-of-geometry trajectory. Interactions with a single rigid post scatter the robot, and these deflections are proportional to the head-post contact duration. The distribution of scattering angles is smooth and strongly-peaked directly behind the post. Interactions with a single row of evenly-spaced posts (with inter-post spacing $d$) produce distributions reminiscent of far-field diffraction patterns: as $d$ decreases, distinct secondary peaks emerge as large deflections become more likely. Surprisingly, we find that the presence of multiple posts does not change the nature of individual collisions; instead, multi-modal scattering patterns arise from multiple posts altering the likelihood of individual collisions to occur. As $d$ decreases, collisions near the leading edges of the posts become more probable, and we find that these interactions are associated with larger deflections. Our results, which highlight the surprising dynamics that can occur during active collisions of self-propelled systems, can inform control principles for locomotors in complex terrain and facilitate design of task-capable active matter.

A Smoothed Particles Hydrodynamics (SPH) method for fluid dynamics is coupled with a rigid and deformable body dynamics solution to yield a framework for solving fluid–solid interaction (FSI) problems. The two-way, force–displacement, coupling of the fluid and solid phases is captured via boundary condition enforcing (BCE) markers. The partial differential equations governing each phase are discretized in space separately and the resulting ordinary and/or algebraic differential equations are integrated in time independently with coupling enforced via fluid–solid boundary conditions. Particular attention is paid to enforcing fluid incompressibility via a projection step that computes the pressure field as the solution of a linear system. The numerical solution leverages hybrid parallel computing: the rigid and flexible body dynamics is handled on the CPU using multiple cores; at the same time, the fluid phase is handled on the graphics processing unit (GPU). The methodology is validated against experimental data and numerical results obtained using two open-source solvers. Several case studies are reported to gauge the accuracy, efficiency, and scalability of the solver. The highlights of the proposed solution are: tight enforcement of fluid incompressibility; ability to handle coupled physics that combines fluid, rigid, and deformable bodies; ability to handle friction and contact; and, scalable implementation that simultaneously employs CPU and GPU computing.

Smoothed particle hydrodynamics (SPH) has been widely applied to flows with free surface, multi-phase flow, and systems with complex boundary geometry. However, it has been shown that SPH suffers from transverse instability when applied to simple wall-bounded shear flows such as Poiseuille and Couette flows at moderate and high Reynolds number, Re≳1, casting the application of SPH to practical situations into doubt, where the Reynolds number is frequently large. Here, we consider Poiseuille flows for a wide range of Reynolds number and find that the documented instability of SPH can be avoided by using appropriate ratio of smoothing length to particle spacing in combination with a density re-initialization technique, which has not been systematically investigated in simulations of simple shear flows. We also probe the source of the instability and point out the limitations of SPH for wall-bounded shear flows at high Reynolds number.

The fluid–solid interaction (FSI) problem is customarily solved by starting with the fluid dynamics component. One chooses an established computational fluid dynamics (CFD) method and subsequently embeds the solid phase dynamics within the CFD solution leading to either a monolithic or a staggered/co-simulated solution. The approach discussed here takes the opposite tack. We start with a differential variational framework to handle the solid phase; i.e., the multi-body dynamics problem in the presence of contact, friction, and bilateral kinematic constraints. The dynamics of the fluid phase, which is captured via smoothed particle hydrodynamics (SPH), is subsequently embedded into this framework in which the incompressibility attribute of the flow is enforced via kinematic constraint equations that involve SPH particles. The resulting monolithic FSI solution methodology relies on a half-implicit symplectic time integration method that uses a matrix-free iterative approach to solve a cone constrained quadratic optimization problem at each time step. This problem yields the contact forces, friction forces, boundary condition Lagrange multipliers, fluid–solid coupling terms, and bilateral constraint Lagrange multipliers. The solution of the optimization problem represents the computationally taxing component of the method. Large integration time steps, tight enforcement of incompressibility, a unified approach for handling the fluid and solid phases, and linear scaling are listed as the attractive attributes of the proposed method. The numerical experiments reported include three validation studies (incompressibility, dam break, and sloshing), a scaling analysis, and a tracked vehicle fording simulation.

We use simulation to gauge how various strategies for purposefully moving in the rain control the degree to which an individual is soaked while getting from point A to point B. The study is only concerned with the number of rain droplet hits. We use this as a proxy for "degree of soaking" without any regard to the clothing that the individual wears. The motion of the individual is assumed not to influence the rain intensity and direction. The two-way coupling emerging at high speeds will be addressed in a different study.

We present a Lagrangian-Lagrangian method for solving Fluid-Solid Interaction (FSI) problems in which the solid phase is deformable/compliant. The fluid phase is modeled using Smoothed Particles Hydrodynamics (SPH); the deformable bodies are modeled with the Absolute Nodal Coordinate Formulation (ANCF). Each phase is integrated implicitly in time and the solutions are coupled explicitly by a force-displacement coupling in which the fluid-on-solid effect is modeled via forces applied to the solid phase; and, the solid-on-fluid effect is modeled via fluid boundary conditions. We validate the formulation against two experimental tests: dam brake and elastic gate analysis.

Collisions with environmental heterogeneities are ubiquitous in living and artificial self-propelled systems. The driven and damped dynamics of such active collisions are fundamentally different from momentum-conserving interactions studied in classical physics. Here we treat such interactions in a scattering framework, studying a sensory-deprived snake-like robot whose lateral undulation scheme typifies a important class of self-propelled systems. During transit through a regular array of posts, interactions between the posts and robot segments reorient the heading, producing scattering patterns reminiscent of those in matter-wave diffraction. As spacing decreases, the robot scatters more strongly; for small inter-post spacing, scattering occurs in preferred directions. Active scattering dynamics are dominated by collisions of the head with a single post; scattering angle correlates with collision duration which in turn is governed by incident undulation phase and post impact location. A model which incorporates these observations reveals that the spacing dependence arises from a remapping of single-post collision states. Our results could lead to simple control schemes for snake-like robots, useful in search and rescue in cluttered environments.

We present the device design, simulation, and measurement results of a therapy device that potentially prevents sleep apnea by slightly increasing inspired CO2 through added dead space (DS). The rationale for treatment of sleep apnea with CO2 manipulation is based on two recently reported premises: (i) preventing transient reductions in PaCO2 will prevent the patient from reaching their apneic threshold, thereby preventing “central” apnea and instabilities in respiratory motor output; and (ii) raising PaCO2 and end-tidal CO2, even by a minimal amount, provides a strong recruitment of upper airway dilator muscles, thereby preventing airway obstruction. We have also provided the simulation results, obtained from solving the Navier–Stokes (NS) equations within the device volume. Therein, the NS equations are coupled with a convection–diffusion equation that represents the transport of CO2 in the device, thus enabling the transient simulation of CO2 propagation. Using this procedure, a prototype of variable volume dead space reservoir device was designed. Volumetric factors influencing carbon dioxide increases in the added reservoir (open-ended DS) were investigated. The maximum/minimum amount of CO2 concentration were obtained for the maximum/minimum device volume; 3.4 and 2.4 mol/m3 for the DS volumes of 1.2 and 0.5 × 10−3 m3, respectively. In all case studies, the CO2 buildup reached a plateau after approximately 20 breathing cycles. The experimental measurement results are in agreement with the simulation and numerical results obtained using the proposed simplified modeling technique, with a maximum relative error of 3.5%.

We summarize and numerically compare two approaches for modeling and simulating the dynamics of dry granular matter. The first one, the discrete-element method via penalty (DEM-P), is commonly used in the soft matter physics and geomechanics communities; it can be traced back to the work of Cundall and Strack [P. Cundall, Proc. Symp. ISRM, Nancy, France 1, 129 (1971); P. Cundall and O. Strack, Geotechnique 29, 47 (1979)GTNQA80016-850510.1680/geot.1979.29.1.47]. The second approach, the discrete-element method via complementarity (DEM-C), considers the grains perfectly rigid and enforces nonpenetration via complementarity conditions; it is commonly used in robotics and computer graphics applications and had two strong promoters in Moreau and Jean [J. J. Moreau, in Nonsmooth Mechanics and Applications, edited by J. J. Moreau and P. D. Panagiotopoulos (Springer, Berlin, 1988), pp. 1-82; J. J. Moreau and M. Jean, Proceedings of the Third Biennial Joint Conference on Engineering Systems and Analysis, Montpellier, France, 1996, pp. 201-208]. The DEM-P and DEM-C are manifestly unlike each other: They use different (i) approaches to model the frictional contact problem, (ii) sets of model parameters to capture the physics of interest, and (iii) classes of numerical methods to solve the differential equations that govern the dynamics of the granular material. Herein, we report numerical results for five experiments: shock wave propagation, cone penetration, direct shear, triaxial loading, and hopper flow, which we use to compare the DEM-P and DEM-C solutions. This exercise helps us reach two conclusions. First, both the DEM-P and DEM-C are predictive, i.e., they predict well the macroscale emergent behavior by capturing the dynamics at the microscale. Second, there are classes of problems for which one of the methods has an advantage. Unlike the DEM-P, the DEM-C cannot capture shock-wave propagation through granular media. However, the DEM-C is proficient at handling arbitrary grain geometries and solves, at large integration step sizes, smaller problems, i.e., containing thousands of elements, very effectively. The DEM-P vs DEM-C comparison is carried out using a public-domain, open-source software package; the models used are available online.

We provide an overview of a multi-physics dynamics engine called Chrono. Its forte is the handling of complex and large dynamic systems containing millions of rigid bodies that interact through frictional contact. Chrono has been recently augmented to support the modeling of fluid-solid interaction (FSI) problems and linear and nonlinear finite element analysis (FEA). We discuss Chrono’s software layout/design and outline some of the modeling and numerical solution techniques at the cornerstone of this dynamics engine. We briefly report on some validation studies that gauge the predictive attribute of the software solution. Chrono is released as open source under a permissive BSD3 license and available for download on GitHub.

We characterize through simulation a microfluidic-based particle sorting approach instrumental in flow cytometry for quantifying microtissue features. The microtissues are represented herein as rigid spheres. The numerical solution employed draws on a Lagrangian-Lagrangian (LL), Smoothed Particle Hydrodynamics (SPH) approach for the simulation of the coupled fluid-rigid-body dynamics. The study sets out to first quantify the influence of the discretization resolution, numerical integration step size, and SPH marker spacing on the accuracy of the numerical solution. By considering the particle motion through the microfluidic device, we report particle surface stresses in the range of sigma = [0.1, 1.0] Pa; i.e., significantly lower than the critical value of 100 Pa that would affect cell viability. Lift-off of non-neutrally buoyant particles in a rectangular channel flow at the target flow regime is investigated to gauge whether the particle shear stress is magnified as a result of dragging on the wall. Several channel designs are considered to assess the effect of channel shape on the performance of the particle sorting device. Moreover, it is shown that a deviation in flow rate does not influence the focusing of the particles at the channel outlet. (C) 2015 Elsevier Ltd. All rights reserved.

Weakly compressible smoothed particle hydrodynamics (WCSPH) has been widely applied to flows with free surfaces, multi-phase flow and systems with complex boundary geometry. It is known, however, that WCSPH suffers from transverse instability when applied to simple wall-bounded shear flows such as Poiseuille and Couette flows at moderate and high Reynolds number, Re & 1, casting the application of WCSPH to practical situations into doubt, where the Reynolds number is frequently large. Here, we consider Poiseuille flow for a wide range of Reynolds number and find that the instability of WCSPH can be avoided by using appropriate ratio of smoothing length to particle spacing in combination with a density re-initialization technique. We also probe the source of the instability and point out the limitations of WCSPH for wall-bounded shear flows at high Reynolds number.