Range Of Possible Designs Research Articles

Deep learning-enabled design for tailored mechanical properties of SLM-manufactured metallic lattice structures

The lattice structures obtained by combining repetitive light cellular forms provide superior high strength to weight capabilities compared to monolithic solid bodies. These properties of lattice structures can be further enhanced by improving the design and manufacturing process. However, the process of creating aluminum alloy lattice structures with tailored mechanical properties is still challenging due to the wide range of possible designs and their complex structure-property relationships. This paper proposes a new methodology that uses the deep learning-based 3D Generative Adversarial Network (3DGAN) model to solve this complex engineering problem. Unlike previous studies on deep learning-based lattice design, the dataset obtained through parametric design and Simulated Annealing techniques enables GAN to create new 3D lattice structures with improved mechanical strength properties. The designs generated with the GAN algorithm were produced using Selective Laser Melting Additive Manufacturing (SLM-AM) technology. The mechanical properties of SLM-fabricated (SLMed) AlSi10Mg unit cell samples were examined by a series of compression and impact tests. The results reveal that the lattice configurations generated using the generative model exhibit improved mechanical properties (e.g., a remarkable increase in normalized energy absorption and extension capacities of up to 57% and 26%, respectively). This study shows that designs generated with the 3DGAN model in lattice structures improve the design space by improving their mechanical properties. Moreover, the successful integration of deep learning and SLM-AM opens up new possibilities for creating custom parts with improved strength-to-weight ratios, dimensional accuracy, and mechanical performance.

Multi-Objective Optimisation of a Novel Bypass Graft with a Spiral Ridge.

The low long-term patency of bypass grafts is a major concern for cardiovascular treatments. Unfavourable haemodynamic conditions in the proximity of distal anastomosis are closely related to thrombus creation and lumen lesions. Modern graft designs address this unfavourable haemodynamic environment with the introduction of a helical component in the flow field, either by means of out-of-plane helicity graft geometry or a spiral ridge. While the latter has been found to lack in performance when compared to the out-of-plane helicity designs, recent findings support the idea that the existing spiral ridge grafts can be further improved in performance through optimising relevant design parameters. In the current study, robust multi-objective optimisation techniques are implemented, covering a wide range of possible designs coupled with proven and well validated computational fluid dynamics (CFD) algorithms. It is shown that the final set of suggested design parameters could significantly improve haemodynamic performance and therefore could be used to enhance the design of spiral ridge bypass grafts.

Teaching Digital Medicine in a Virtual Classroom: Impacts on Student Mindset and Competencies.

Digital competencies, as well as knowledge about digital medicine, are becoming increasingly relevant but are rarely reflected in teaching concepts at universities. One reason for this is probably the fact that they are not yet part of the curricula in many areas or countries (such as medicine in Germany). Therefore, courses that address digital competencies and intend to impart knowledge about digital medicine are not subject to any curricular specifications and have a correspondingly broad range of possible designs. This article reports findings from an investigation on an interdisciplinary and cross-faculty course on digital medicine. An online questionnaire was used to assess student attitudes toward digital medicine topics and conduct self-assessments of their digital competencies before and after the course. The aim of this study was to test whether such a course could influence students' attitudes and competencies. Group comparisons revealed statistically significant changes. They proved that the described course and its content regarding digital transformation in healthcare and digital medicine had an impact on digital competencies and participant opinions on digital topics. In order to teach students important competencies for the 21st century, universities should offer more courses that address digital transformation and support students in improving their competencies.

Improving adaptive seamless designs through Bayesian optimization.

We propose to use Bayesian optimization (BO) to improve the efficiency of the design selection process in clinical trials. BO is a method to optimize expensive black-box functions, by using a regression as a surrogate to guide the search. In clinical trials, planning test procedures and sample sizes is a crucial task. A common goal is to maximize the test power, given a set of treatments, corresponding effect sizes, and a total number of samples. From a wide range of possible designs, we aim to select the best one in a short time to allow quick decisions. The standard approach to simulate the power for each single design can become too time consuming. When the number of possible designs becomes very large, either large computational resources are required or an exhaustive exploration of all possible designs takes too long. Here, we propose to use BO to quickly find a clinical trial design with high power from a large number of candidate designs. We demonstrate the effectiveness of our approach by optimizing the power of adaptive seamless designs for different sets of treatment effect sizes. Comparing BO with an exhaustive evaluation of all candidate designs shows that BO finds competitive designs in a fraction of thetime.

A stochastically curtailed single‐arm phase II trial design for binary outcomes

ABSTRACT Phase II clinical trials are a critical aspect of the drug development process. With drug development costs ever increasing, novel designs that can improve the efficiency of phase II trials are extremely valuable. Phase II clinical trials for cancer treatments often measure a binary outcome. The final trial decision is generally to continue or cease development. When this decision is based solely on the result of a hypothesis test, the result may be known with certainty before the planned end of the trial. Unfortunately, there is often no opportunity for early stopping when this occurs. Some existing designs do permit early stopping in this case, accordingly reducing the required sample size and potentially speeding up drug development. However, more improvements can be achieved by stopping early when the final trial decision is very likely, rather than certain, known as stochastic curtailment. While some authors have proposed approaches of this form, these approaches have various limitations. In this work we address these limitations by proposing new design approaches for single-arm phase II binary outcome trials that use stochastic curtailment. We use exact distributions, avoid simulation, consider a wider range of possible designs and permit early stopping for promising treatments. As a result, we are able to obtain trial designs that have considerably reduced sample sizes on average.

Designing the design of experiments (DOE) – An investigation on the influence of different factorial designs on the characterization of complex systems

Although a general set of guidelines and procedures for performing the design of experiments (DOE) exists, the literature lacks a recommended course of action for finding and selecting the optimal design of experiments among a large range of possible designs. This research tries to fill this gap by comprehensively testing more than thirty different DOEs through nearly half a million simulated experimental runs. The performance of various DOEs in the characterization of the thermal behaviour of a double skin façade (DSF) is assessed by comparing the outcomes of the different designs and using the full factorial design (FFD) as the ground truth. Besides the finding for the specific case study used in this investigation, this research allowed us to obtain some broad conclusions on the behaviour of different DOEs, which are summarized and translated into recommendations and a general decision tree chart for selecting the suitable DOE(s). The outcomes of this study help researchers and designers to apply DOEs that consider the extent of nonlinearity and interaction of factors in the investigated process in order to select the most successful and the most efficient designs for the specific process characterization.

Selective single-atom electrocatalysts: a review with a focus on metal-doped covalent triazine frameworks.

Single-atom electrocatalysts (SACs), which comprise singly isolated metal sites supported on heterogeneous substrates, have attracted considerable recent attention as next-generation electrocatalysts for various key reactions from the viewpoint of the environment and energy. Not only electrocatalytic activity but also selectivity can be precisely tuned via the construction of SACs with a defined coordination structure, such as homogeneous organometallics. Covalent organic frameworks (COFs) are promising supports for single-atom sites with designed coordination environments due to their unique physicochemical properties, which include porous structures, robustness, a wide range of possible designs, and abundant heteroatoms to coordinate single-metal sites. The rigid frameworks of COFs can hold unstable single-metal atoms, such as coordinatively unsaturated sites or easily aggregated Pt-group metals, which exhibit unique electrocatalytic selectivity. This minireview summarizes recent advances in the selective reactions catalysed by SACs, mainly those supported on triazine-based COFs.

Multimaterial Control of Instability in Soft Mechanical Metamaterials

Soft mechanical metamaterials working on the basis of instability have numerous potential applications in the context of machine materials. Controlling the onset of instability is usually required when rationally designing such metamaterials. We study the isolated and modulated effects of geometrical design and material distribution on the onset of instability in multimaterial cellular metamaterials. We use multimaterial additive manufacturing to fabricate cellular specimens whose unit cells are divided into void space, a square element, and an intermediate ligament. The ratio of the elastic modulus of the ligament to that of the square element [(EL)/(ES)] is changed by using different material types. Computational models are also developed, validated against experimental observations, and used to study a wide range of possible designs. The critical stress can be adjusted independently from the critical strain by changing the material type while keeping [(EL)/(ES)] constant. The critical strain shows a power-law relationship with [(EL)/(ES)] within the range [(EL)/(ES)]=0.1-10. The void shape design alters the critical strain by up to threefold, while the combined effects of the void shape and material distribution cause up to a ninefold change in the critical strain. Our findings highlight the strong influence of material distribution on the onset of the instability and buckling mode.

Modeling the Heavens: Sphairopoiia and Ptolemy’s Planetary Hypotheses

This article investigates sphairopoiia, the art of making instruments that display the heavens, in Claudius Ptolemy’s Planetary Hypotheses. It takes up two questions: what kind of instrument does Ptolemy describe? And, could such an instrument have been constructed? I argue that Ptolemy did not propose one specific type of instrument, but instead he offered a range of possible designs, with the details to be worked out by the craftsman. Moreover, in addition to exhibiting his astronomical models and having the ability to estimate predictions, the instrument he proposed would have also shown the physical workings of the heavens. What emerges is both a clearer idea of what Ptolemy wanted the technician to build, and the purpose of such instruments.

Mitigation of railway induced ground vibration by heavy masses next to the track

The effectiveness of heavy masses next to the track as a measure for the reduction of railway induced ground vibration is investigated by means of numerical simulations. It is assumed that the heavy masses are placed in a continuous row along the track forming a wall. Such a continuous wall could be built as a gabion wall and also used as a noise barrier. Since the performance of mitigation measures on the transmission path strongly depends on local ground conditions, a parametric study is performed for a range of possible designs in a set of different ground types. A two-and-a-half dimensional coupled finite element–boundary element methodology is used, assuming that the geometry of the problem is uniform in the direction along the track. It is found that the heavy masses start to be effective above the mass–spring resonance frequency which is determined by the dynamic stiffness of the soil and the mass of the wall. At frequencies above this resonance frequency, masses at the soil׳s surface hinder the propagation of surface waves. It is therefore beneficial to make the footprint of the masses as large and stiff as possible. For homogeneous soil conditions, the effectiveness is nearly independent of the distance behind the wall. In the case of a layered soil with a soft top layer, the vibration reduction strongly decreases with increasing distance from the wall.

Enhancing the Economic Competitiveness of Concentrating Solar Power Plants Through an Innovative Integrated Solar-Combined Cycle With Thermal Energy Storage

The present work deals with the thermo-economic analysis of an innovative combined power cycle consisting of a molten-salt solar tower power plant with storage supported by additional heat provided from the exhaust of a topping gas-turbine unit. A detailed dynamic model has been elaborated using an in house simulation tool that simultaneously encompasses meteorological, demand and price data. A wide range of possible designs are evaluated in order to show the trade-offs between the objectives of achieving sustainable and economically competitive designs. Results show that optimal designs of the novel concept are a promising cost-effective hybrid option that can successfully fulfill both the roles of a gas peaker plant and a baseload solar power plant in a more effective manner. Moreover, designs are also compared against conventional combined cycle gas turbine (CCGT) power plants and it is shown that, under specific peaking operating strategies (P-OSs), the innovative concept cannot only perform better from an environmental standpoint but also economically.

Improving Intersection Design Practices

This study aims to use operational characteristics to help determine the size and the design of intersections on the basis of a targeted level of operation. This approach will allow for a preliminary evaluation of a broader range of possible designs, by screening out those designs considered less desirable or inappropriate on the basis of operational performance. This approach will also allow for a more objective comparison of all alternatives because all options target the same operational service level. The use of the critical lane analysis method was considered an appropriate approach for developing such size estimates for intersections. Similar methods for stop-controlled and yield-controlled intersections were also identified because it was necessary to expand these methods to include unsignalized designs as well. The Intersection Design Alternative Tool developed through this effort is capable of evaluating 13 intersection alternatives and identifying preferred lane configurations from more than 12,000 available configurations.

Estimation and Confidence Regions for Multi‐Dimensional Effective Dose

The problem of finding confidence regions for multiple predictor variables corresponding to given expected values of a response variable has not been adequately resolved. Motivated by an example from a study on hyperbaric exposure using a logistic regression model, we develop a conceptual framework for the estimation of the multi-dimensional effective dose for binary outcomes. The k -dimensional effective dose can be determined by conditioning on k - 1 components and solving for the last component as a conditional univariate effective dose. We consider various approaches for calculating confidence regions for the multi-dimensional effective dose and compare them via a simulation study for a range of possible designs. We analyze data related to decompression sickness to illustrate our procedure. Our results provide a practical approach to finding confidence regions for predictor variables for a given response value.

Reliability of Steel Doweled Wood Connections Designed to ASCE 16-95

First-order reliability analyses were performed for wood connections, using bolts, nails, lag screws, and wood screws, including both wood and steel side plates, designed to ASCE 16-95. The reliability analyses were performed using the European yield model to determine the connection capacity. Using reasonable statistics for the random variables in the yield equations, a reliability index was determined for each of the possible failure modes for both single and double shear connections. Simple bounds were then determined for the reliability index of the series system consisting of multiple failure modes. These reliability analyses show that designs to ASCE 16-95 do not exhibit consistent reliability across the range of possible designs. One way to increase consistency is to use the full set of yield equations rather than the simplified set of design equations now present in ASCE 16-95 for most of the connectors. Other modifications may also be necessary since there are inconsistent reliability levels even for those connectors designed to the full set of equations.

Patterns of convergence in general shell form among Paleozoic gastropods

Abstract Recent phylogenetic studies of Paleozoic gastropods show the classification provided by the Treatise on Invertebrate Paleontology to include numerous highly polyphyletic taxa. Here we test whether this classification reflects limits on the range of possible designs, general architectural constraints, or common functional solutions for Paleozoic gastropods. Our test evaluates whether superfamilial/subordinal level archetypes as defined by the Treatise evolved more frequently than expected among 626 Late Cambrian–Middle Devonian species. Using a previously established phylogeny and five general shell features (spire angle, exhalent current position, base angle, umbilical width, and apertural inclination) we show that there are fewer gastropod morphotypes than expected given the frequency of change in these features. This is true even after accounting for architectural constraints implied by the data. Moreover, the most common morphotypes include significantly more species and evolved significantly ...

A deterministic algorithm for experimental design applied to tomographic and microseismic monitoring surveys

SUMMARY Most general experimental design algorithms are either: (i) stochastic and hence give different designs each time they are run with finite computing power, or (ii) deterministic but converge to results that depend on an initial or reference design, taking little or no account of the range of all other possible designs. In this paper we introduce an approximation to standard measures of experimental design quality that enables a new algorithm to be used. The algorithm is simple, deterministic and the resulting experimental design is influenced by the full range of possible designs, thus addressing problems (i) and (ii) above. Although the designs produced are not guaranteed to be globally optimal, they significantly increase the magnitude of small eigenvalues in the model‐data relationship (without requiring that these eigenvalues be calculated). This reduces the model uncertainties expected post-experiment. We illustrate the method on simple tomographic and microseismic location examples with varying degrees of seismic attenuation.

Design of nonminimum phase processes for optimal switchability

Based on a method for the evaluation of switchability for nonlinear nonminimum phase processes with input multiplicity, a design method is presented that determines the optimal design with respect to switchability out of a range of possible designs. An optimal control problem formulation determines a stable approximate inverse of the process in order to evaluate the limitations that are imposed by the presence of nonminimum phase behaviour and input multiplicity on the different designs. The approach is illustrated on a case study involving the design of a system with reactor and separator. It showed that a different design is preferred for switchability between two operating points than for controllability around the basic operating point. The optimal design for controllability around a steady state is minimum phase, whereas the design for optimal switchability is nonminimum phase at both operating points. The importance of considering dynamic aspects at the design stage is illustrated with this study.

Progress in stacked piezocomposite ultrasonic transducers for low frequency applications

A stacked ultrasonic transducer comprises multiple individual layers connected mechanically in series and electrically in parallel to reduce the fundamental thickness mode resonance to a frequency corresponding to the transit time of the complete stack and the electrical impedance to a value which corresponds to that of the layers of the stack in parallel. In turn, this allows lower frequency resonant operation than would be possible with a single layer, and facilitates electrical impedance matching to typical transmission circuitry. On transmission, an ideal stack of uniform layers will have an output amplitude larger than that of the equivalent single layer by a factor equal to the . However, using conventional signal amplification circuitry on reception, the output voltage amplitude will be smaller than that of the equivalent single layer by a similar factor. In the past, stacks have commonly been assembled from layers of conventional piezoceramic material but more recently there have been reports of stacks of 1–3 piezocomposites and it is this type that is considered here. The work described in this paper is motivated by the need to operate at frequencies lower than are possible using conventional piezocomposite fabrication technology. Progress in comparison of experimental and simulated results is outlined and the highlights of a theoretical design study are presented. These show that although the general behaviour of a stacked structure is easily predicted, a rigorous theoretical analysis is essential to understand the detail of even a limited range of possible designs.

Signal processing of ultrasonic signals with applications to surface metrology

A stacked ultrasonic transducer comprises multiple individual layers connected mechanically in series and electrically in parallel to reduce the fundamental thickness mode resonance to a frequency corresponding to the transit time of the complete stack and the electrical impedance to a value which corresponds to that of the layers of the stack in parallel. In turn, this allows lower frequency resonant operation than would be possible with a single layer, and facilitates electrical impedance matching to typical transmission circuitry. On transmission, an ideal stack of uniform layers will have an output amplitude larger than that of the equivalent single layer by a factor equal to the . However, using conventional signal amplification circuitry on reception, the output voltage amplitude will be smaller than that of the equivalent single layer by a similar factor. In the past, stacks have commonly been assembled from layers of conventional piezoceramic material but more recently there have been reports of stacks of 1–3 piezocomposites and it is this type that is considered here. The work described in this paper is motivated by the need to operate at frequencies lower than are possible using conventional piezocomposite fabrication technology. Progress in comparison of experimental and simulated results is outlined and the highlights of a theoretical design study are presented. These show that although the general behaviour of a stacked structure is easily predicted, a rigorous theoretical analysis is essential to understand the detail of even a limited range of possible designs.

Conditional Markov Chain Design for Accrual Clinical Trials

Randomization in a comparative experiment has, as one aim, the control of bias in the initial selection of experimental units. When the experiment is a clinical trial employing the accrual of patients, two additional aims are the control of admission bias and control of chronologic bias. This can be accomplished by using a method of randomization, such as the “biased coin design” of Efron, which sequentially forces balance.As an extension of Efron's design, this paper develops a class of conditional Markov chain designs. The detailed randomization employed utilizes the sequential imbalances in the treatment allocation as states in a Markov process. Through the use of appropriate transition probabilities, a range of possible designs can be attained.An additional objective of physical randomization is to provide a model for data analysis. Such a randomization theoretic analysis is presented for the current designs. In addition, Monte Carlo sampling results are given to support the proposed normal theory approximation to the exact randomization distribution.