Hasil untuk "Mechanics of engineering. Applied mechanics"

Vignesh Sompur, Varadhan Skm, Asokan Thondiyath

Dexterous prosthetic hands with a simple design are the need of the hour. The limiting factor for prosthetic hands is the structure, functionality, and control of the fingers and the thumb. Traditionally, robotic fingers used in prosthetic hands are tendon-driven or have linkage-based mechanisms. While tendon-driven mechanisms provide anthropomorphic behaviour, they lack sufficient grip force. In contrast, linkage mechanisms develop sufficient grip force but at the expense of the size and weight of the overall design. Further, a linkage-based mechanism provides only shape adaptation without joint coupling. To address this gap in prosthetic finger design, we propose a novel underactuated, hybrid, and minimalistic finger mechanism to achieve simultaneous coupling and self-adaptation. The designed finger mechanism has three degrees of freedom provided by two 4-bar mechanisms in series, with two degrees of actuation. The finger is actuated through a pair of inelastic tendons acting on two joints. The tendon architecture is bio-inspired and improves the finger mechanism’s anthropomorphic behaviour. A detailed kinematic and static analysis is provided to describe the finger design’s operating principle and construction. Simulations of fingertip trajectory and contact forces are also performed. Additionally, a prototype of the mechanism was 3D printed to validate the design of the finger. Grasping simulations and experiments were also performed for a typical 4-bar-based finger mechanism. The results show improved anthropomorphic motion and increased contact forces for the current finger design compared to the conventional 4-bar mechanism-based prosthetic finger.

Jaehyun Lee, Kisoo Park, Eui Seung Son et al.

Large-sized ground telescopes have been developed to meet the high demands for opto-mechanical imaging systems in space and military applications. In line with these advancements, we developed a 1-m class ground telescope for astronomical imaging and satellite laser ranging (SLR). In a ground telescope, mirror deflection is mainly induced by gravity and temperature change. In particular, the gravity vector varies depending on the pointing direction of a telescope, so the surface deformations of the mirrors due to self-gravity need to be managed in different observation directions. This study introduces a mechanical design for an optical tube assembly (OTA) and suggests an optimized design for the secondary mirror (M2) assembly. For a kinematic positioning of the M2, its lightweight was achieved based on the partially open-back structure with hexagonal pocket cells. Then, we optimized the flexure mount design with a bipod structure to minimize the surface errors (SFEs) of the M2 in both the horizontal and vertical pointing directions. Additionally, we simulated the deflections of the primary mirror (M1) and M2 assemblies when installed on the telescope. Based on our design, the M2 was fabricated and processed, and we demonstrated its assembly process and surface quality test.

Nasir U. Eisty, Jeffrey C. Carver, Johanna Cohoon et al.

In the evolving landscape of scientific and scholarly research, effective collaboration between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) is pivotal for advancing innovation and ensuring the integrity of computational methodologies. This paper presents ten strategic guidelines aimed at fostering productive partnerships between these two distinct yet complementary communities. The guidelines emphasize the importance of recognizing and respecting the cultural and operational differences between RSEs and SERs, proactively initiating and nurturing collaborations, and engaging within each other's professional environments. They advocate for identifying shared challenges, maintaining openness to emerging problems, ensuring mutual benefits, and serving as advocates for one another. Additionally, the guidelines highlight the necessity of vigilance in monitoring collaboration dynamics, securing institutional support, and defining clear, shared objectives. By adhering to these principles, RSEs and SERs can build synergistic relationships that enhance the quality and impact of research outcomes.

Nils Much, Magdalena Schreter-Fleischhacker, Peter Munch et al.

Abstract Computational modeling of the melt pool dynamics in laser-based powder bed fusion metal additive manufacturing (PBF-LB/M) promises to shed light on fundamental mechanisms of defect generation. These processes are accompanied by rapid evaporation so that the evaporation-induced recoil pressure and cooling arise as major driving forces for fluid dynamics and temperature evolution. The magnitude of these interface fluxes depends exponentially on the melt pool surface temperature, which, therefore, has to be predicted with high accuracy. The present work utilizes a diffuse interface finite element model based on a continuum surface flux (CSF) description of interface fluxes to study dimensionally reduced thermal two-phase problems representative for PBF-LB/M in a finite element framework. It is demonstrated that the extreme temperature gradients combined with the high ratios of material properties between metal and ambient gas lead to significant errors in the interface temperatures and fluxes when classical CSF approaches, along with typical interface thicknesses and discretizations, are applied. It is expected that this finding is also relevant for other types of diffuse interface PBF-LB/M melt pool models. A novel parameter-scaled CSF approach is proposed, which is constructed to yield a smoother temperature field in the diffuse interface region, significantly increasing the solution accuracy. The interface thickness required to predict the temperature field with a given level of accuracy is less restrictive by at least one order of magnitude for the proposed parameter-scaled approach compared to classical CSF, drastically reducing computational costs. Finally, we showcase the general applicability of the parameter-scaled CSF to a 3D simulation of stationary laser melting of PBF-LB/M considering the fully coupled thermo-hydrodynamic multi-phase problem, including phase change.

Md. Niamat Ullah, Hasan Mahmud Ornok, Sharmin Sultana et al.

In order to systematically investigate the correlating capability of viscosity models, six well-known correlative models of Grunberg-Nissan (GN), Hind (HND), Heric (HRC), Ausländer (AUS) for dynamic viscosity, η, and McAllister 3-body (MAC3) and McAllister 4-body (MAC4) for kinematic viscosity, ν, were employed and tested for viscosity data of 83 organic binary liquid systems consisting of 33 different aromatic hydrocarbons (ArH), alkanes (RH), cycloalkanes (CyRH) and alkanols (ROH). Keeping ArH as a common component and increasing the chain length of other components, the systems were categorized as Category 1: ArH + RH, Category 2: ArH + CyRH, Category 3: ArH + ArH and Category 4: ArH + ROH. For all the models fitting parameters along with the statistical parameters such as SPD σ(%), ASPD σ(%), OASPD σ(%) and GOASPD σ(%) were computed by the  Nonlinear Least Squares Minimization (NLSM) technique with the ‘Solver’ add-in package. Among the four categories, Category 3, OASPD, σ(%) values lie between 0.16 and 0.21, indicating that all the models fitted extremely well. However, for dynamic viscosities, the η AUS model demonstrated the best correlating capabilities with GOASPD σ(%) of 0.48, while the HND model performed the poorest with GOASPD σ(%) at 3.8. For the kinematic viscosities, ν in both the MAC3 and MAC4 models yielded satisfactory results with GOASPD σ(%) as < 1.0 %.

Alessandra Aimi, Giulia Di Credico, Heiko Gimperlein

This article studies a boundary element method for dynamic frictional contact between linearly elastic bodies. We formulate these problems as a variational inequality on the boundary, involving the elastodynamic Poincaré-Steklov operator. The variational inequality is solved in a mixed formulation using boundary elements in space and time. In the model problem of unilateral Tresca friction contact with a rigid obstacle we obtain an a priori estimate for the resulting Galerkin approximations. Numerical experiments in two space dimensions demonstrate the stability, energy conservation and convergence of the proposed method for contact problems involving concrete and steel in the linearly elastic regime. They address both unilateral and two-sided dynamic contact with Tresca or Coulomb friction.

Oleksandr Kosenkov, Michael Unterkalmsteiner, Jannik Fischbach et al.

Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for approaches to regulatory Requirements Engineering (RE) covering and integrating both legal and engineering perspectives. Problem: Regulatory RE approaches need to capture and reflect both the elementary concepts and relationships from a legal perspective and their seamless transition to concepts used to specify software requirements. No existing approach considers explicating and managing legal domain knowledge and engineering-legal coordination. Method: We conducted focus group sessions with legal researchers to identify the core challenges to establishing a regulatory RE approach. Based on our findings, we developed a candidate solution and conducted a first conceptual validation to assess its feasibility. Results: We introduce the first version of our Artifact Model for Regulatory Requirements Engineering (AM4RRE) and its conceptual foundation. It provides a blueprint for applying legal (modelling) concepts and well-established RE concepts. Our initial results suggest that artifact-centric RE can be applied to managing legal domain knowledge and engineering-legal coordination. Conclusions: The focus groups that served as a basis for building our model and the results from the expert validation both strengthen our confidence that we already provide a valuable basis for systematically integrating legal concepts into RE. This overcomes contemporary challenges to regulatory RE and serves as a basis for exposure to critical discussions in the community before continuing with the development of tool-supported extensions and large-scale empirical evaluations in practice.

Adrian Bajraktari, Michelle Binder, Andreas Vogelsang

Modern science is relying on software more than ever. The behavior and outcomes of this software shape the scientific and public discourse on important topics like climate change, economic growth, or the spread of infections. Most researchers creating software for scientific purposes are not trained in Software Engineering. As a consequence, research software is often developed ad hoc without following stringent processes. With this paper, we want to characterize research software as a new application domain that needs attention from the Requirements Engineering community. We conducted an exploratory study based on 8 interviews with 12 researchers who develop software. We describe how researchers elicit, document, and analyze requirements for research software and what processes they follow. From this, we derive specific challenges and describe a vision of Requirements Engineering for research software.

R. Huiskes, E. Chao

Jan Heine, Herbert Palm

The increasing pressure within VUCA (volatility, uncertainty, complexity and ambiguity) driven environments causes traditional, plan-driven Systems Engineering approaches to no longer suffice. Agility is then changing from a "nice-to-have" to a "must-have" capability for successful system developing organisations. The current state of the art, however, does not provide clear answers on how to map this need in terms of processes, methods, tools and competencies (PMTC) and how to successfully manage the transition within established industries. In this paper, we propose an agile Systems Engineering (SE) Framework for the automotive industry to meet the new agility demand. In addition to the methodological background, we present results of a pilot project in the chassis development department of a German automotive manufacturer and demonstrate the effectiveness of the newly proposed framework. By adopting the described agile SE Framework, companies can foster innovation and collaboration based on a learning, continuous improvement and self-reinforcing base.

Marcel Grote, Justus Bogner

Today, many systems use artificial intelligence (AI) to solve complex problems. While this often increases system effectiveness, developing a production-ready AI-based system is a difficult task. Thus, solid AI engineering practices are required to ensure the quality of the resulting system and to improve the development process. While several practices have already been proposed for the development of AI-based systems, detailed practical experiences of applying these practices are rare. In this paper, we aim to address this gap by collecting such experiences during a case study, namely the development of an autonomous stock trading system that uses machine learning functionality to invest in stocks. We selected 10 AI engineering practices from the literature and systematically applied them during development, with the goal to collect evidence about their applicability and effectiveness. Using structured field notes, we documented our experiences. Furthermore, we also used field notes to document challenges that occurred during the development, and the solutions we applied to overcome them. Afterwards, we analyzed the collected field notes, and evaluated how each practice improved the development. Lastly, we compared our evidence with existing literature. Most applied practices improved our system, albeit to varying extent, and we were able to overcome all major challenges. The qualitative results provide detailed accounts about 10 AI engineering practices, as well as challenges and solutions associated with such a project. Our experiences therefore enrich the emerging body of evidence in this field, which may be especially helpful for practitioner teams new to AI engineering.

Hari Krishna Hari Prasad, Ross L. Hatton, Kaushik Jayaram

Discrete and periodic contact switching is a key characteristic of steady-state legged locomotion. This paper introduces a framework for modeling and analyzing this contact-switching behavior through the framework of geometric mechanics on a toy robot model that can make continuous limb swings and discrete contact switches. The kinematics of this model form a hybrid shape-space and by extending the generalized Stokes' theorem to compute discrete curvature functions called \textit{stratified panels}, we determine average locomotion generated by gaits spanning multiple contact modes. Using this tool, we also demonstrate the ability to optimize gaits based on the system's locomotion constraints and perform gait reduction on a complex gait spanning multiple contact modes to highlight the method's scalability to multilegged systems.

Bishal Lakha, Kalyan Bhetwal, Nasir U. Eisty

Context: On top of the inherent challenges startup software companies face applying proper software engineering practices, the non-deterministic nature of machine learning techniques makes it even more difficult for machine learning (ML) startups. Objective: Therefore, the objective of our study is to understand the whole picture of software engineering practices followed by ML startups and identify additional needs. Method: To achieve our goal, we conducted a systematic literature review study on 37 papers published in the last 21 years. We selected papers on both general software startups and ML startups. We collected data to understand software engineering (SE) practices in five phases of the software development life-cycle: requirement engineering, design, development, quality assurance, and deployment. Results: We find some interesting differences in software engineering practices in ML startups and general software startups. The data management and model learning phases are the most prominent among them. Conclusion: While ML startups face many similar challenges to general software startups, the additional difficulties of using stochastic ML models require different strategies in using software engineering practices to produce high-quality products.

Daxing Lei, Hang Lin, Yixian Wang