Machine Learning for RANS Turbulence Modelling of Variable Property Flows

This paper presents a machine learning methodology to improve the predictions of traditional RANS turbulence models in channel flows subject to strong variations in their thermophysical properties. The developed formulation contains several improvements over the existing Field Inversion Machine Learning (FIML) frameworks described in the literature, as well as the derivation of a new modelling technique. We first showcase the use of efficient optimization routines to automatize the process of field inversion in the context of CFD, combined with the use of symbolic algebra solvers to generate sparse-efficient algebraic formulas to comply with the discrete adjoint method. The proposed neural network architecture is characterized by the use of an initial layer of logarithmic neurons followed by hyperbolic tangent neurons, which proves numerically stable. The machine learning predictions are then corrected using a novel weighted relaxation factor methodology, that recovers valuable information from otherwise spurious predictions. The study uses the K-fold cross-validation technique, which is beneficial for small datasets. The results show that the machine learning model acts as an excellent non-linear interpolator for DNS cases well-represented in the training set, and that moderate improvement margins are obtained for sparser DNS cases. It is concluded that the developed machine learning methodology corresponds to a valid alternative to improve RANS turbulence models in flows with strong variations in their thermophysical properties without introducing prior modeling assumptions into the system

Transient growth in diabatic boundary layers with fluids at supercritical pressure

In the region close to the thermodynamic critical point and in the proximity of the pseudo-boiling (Widom) line, strong property variations substantially alter the growth of modal instabilities, as revealed in Ren et al. (J. Fluid Mech., vol. 871, 2019, pp. 831-864). Here, we study non-modal disturbances in the spatial framework using an eigenvector decomposition of the linearized Navier-Stokes equations under the assumption of locally parallel flow. The boundary layers with the fluid at supercritical pressure are heated or cooled by prescribing the wall and free-stream temperatures so that the temperature profile is either entirely subcritical (liquid-like), supercritical (gas-like), or transcritical (across the Widom line). The free-stream Mach number is set to $10^{-3}$. In the non-transcritical regimes, the resulting streamwise-independent streaks originate from the lift-up effect. Wall cooling enhances the energy amplification for both subcritical and supercritical regimes. When the temperature profile is increased beyond the Widom line, a strong sub-optimal growth is observed over very short streamwise distances due to the Orr mechanism. The non-modal growth is put in perspective with modal growth by means of an $N$-factor comparison. In the non-transcritical regimes, modal stability dominates regardless of a wall-temperature variation. In contrast, in the transcritical regime, non-modal $N$-factors are found to resemble the imposition of an adverse pressure gradient in the ideal-gas regime. When cooling beyond the Widom line, optimal growth is greatly enhanced, yet strong inviscid instability prevails. When heating beyond the Widom line, optimal growth could be sufficiently large to favor transition, particularly with a high free-stream turbulence level

Combined effects of stress and temperature on hydrogen diffusion in non-hydride forming alloys applied in gas turbines

Hydrogen plays a vital role in the utilisation of renewable energy, but ingress and diffusion of hydrogen in a gas turbine can induce hydrogen embrittlement on its metallic components. This paper aims to investigate the hydrogen transport in a non-hydride forming alloy such as Alloy 690 used in gas turbines inspired by service conditions of turbine blades, i.e. under the combined effects of stress and temperature. An appropriate hydrogen transport equation is formulated, accounting for both stress and temperature distributions of the domain in the non-hydride forming alloy. Finite element (FE) analyses are performed to predict steady-state hydrogen distribution in lattice sites and dislocation traps of a double notched specimen under constant tensile load and various temperature fields. Results demonstrate that the lattice hydrogen concentration is very sensitive to the temperature gradients, whilst the stress concentration only slightly increases local lattice hydrogen concentration. The combined effects of stress and temperature result in the highest concentration of the dislocation trapped hydrogen in low-temperature regions, although the plastic strain is only at a moderate level. Our results suggest that temperature gradients and stress concentrations in turbine blades due to cooling channels and holes make the relatively low-temperature regions susceptible to hydrogen embrittlement

Edge Transfer Lithography Using Alkanethiol Inks

Edge lithographic patterning techniques are based on the utilization of the edges of micrometer-sized template features for the reproduction of submicrometer structures. Edge transfer lithography (ETL) permits local surface modification in a single step by depositing self-assembled monolayers onto a metal substrate selectively along the feature edges of an elastomeric stamp. In this report two stamp designs are described that now allow for the use of alkanethiol inks in ETL and their use as etch resists to reproduce submicrometer structures in gold. Anisotropically modified stamps are shown to combine the potential for very high-resolution patterning with the versatility and simplicity of microcontact printing

Clinical consequences of diagnostic variability in the histopathological evaluation of early rectal cancer

Introduction: In early rectal cancer, organ sparing treatment strategies such as local excision have gained popularity. The necessity of radical surgery is based on the histopathological evaluation of the local excision specimen. This study aimed to describe diagnostic variability between pathologists, and its impact on treatment allocation in patients with locally excised early rectal cancer. Materials and methods: Patients with locally excised pT1-2 rectal cancer were included in this prospective cohort study. Both quantitative measures and histopathological risk factors (i.e. poor differentiation, deep submucosal invasion, and lymphatic- or venous invasion) were evaluated. Interobserver variability was reported by both percentages and Fleiss’ Kappa- (ĸ) or intra-class correlation coefficients. Results: A total of 126 patients were included. Ninety-four percent of the original histopathological reports contained all required parameters. In 73 of the 126 (57.9%) patients, at least one discordant parameter was observed, which regarded histopathological risk factors for lymph node metastases in 36 patients (28.6%). Interobserver agreement among different variables varied between 74% and 95% or ĸ 0.530–0.962. The assessment of lymphovascular invasion showed discordances in 26% (ĸ = 0.530, 95% CI 0.375–0.684) of the cases. In fourteen (11%) patients, discordances led to a change in treatment strategy. Conclusion: This study demonstrated that there is substantial interobserver variability between pathologists, especially in the assessment of lymphovascular invasion. Pathologists play a key role in treatment allocation after local excision of early rectal cancer, therefore interobserver variability needs to be reduced to decrease the number of patients that are over- or undertreated.</p

Clinical consequences of diagnostic variability in the histopathological evaluation of early rectal cancer

Introduction: In early rectal cancer, organ sparing treatment strategies such as local excision have gained popularity. The necessity of radical surgery is based on the histopathological evaluation of the local excision specimen. This study aimed to describe diagnostic variability between pathologists, and its impact on treatment allocation in patients with locally excised early rectal cancer. Materials and methods: Patients with locally excised pT1-2 rectal cancer were included in this prospective cohort study. Both quantitative measures and histopathological risk factors (i.e. poor differentiation, deep submucosal invasion, and lymphatic- or venous invasion) were evaluated. Interobserver variability was reported by both percentages and Fleiss’ Kappa- (ĸ) or intra-class correlation coefficients. Results: A total of 126 patients were included. Ninety-four percent of the original histopathological reports contained all required parameters. In 73 of the 126 (57.9%) patients, at least one discordant parameter was observed, which regarded histopathological risk factors for lymph node metastases in 36 patients (28.6%). Interobserver agreement among different variables varied between 74% and 95% or ĸ 0.530–0.962. The assessment of lymphovascular invasion showed discordances in 26% (ĸ = 0.530, 95% CI 0.375–0.684) of the cases. In fourteen (11%) patients, discordances led to a change in treatment strategy. Conclusion: This study demonstrated that there is substantial interobserver variability between pathologists, especially in the assessment of lymphovascular invasion. Pathologists play a key role in treatment allocation after local excision of early rectal cancer, therefore interobserver variability needs to be reduced to decrease the number of patients that are over- or undertreated.</p

Patients’ perspectives and the perceptions of healthcare providers in the treatment of early rectal cancer; a qualitative study

Background: Shared decision-making has become of increased importance in choosing the most suitable treatment strategy for early rectal cancer, however, clinical decision-making is still primarily based on physicians’ perspectives. Balancing quality of life and oncological outcomes is difficult, and guidance on patients’ involvement in this subject in early rectal cancer is limited. Therefore, this study aimed to explore preferences and priorities of patients as well as physicians’ perspectives in treatment for early rectal cancer. Methods: In this qualitative study, semi-structured interviews were performed with early rectal cancer patients (n = 10) and healthcare providers (n = 10). Participants were asked which factors influenced their preferences and how important these factors were. Thematic analyses were performed. In addition, participants were asked to rank the discussed factors according to importance to gain additional insights. Results: Patients addressed the following relevant factors: the risk of an ostomy, risk of poor bowel function and treatment related complications. Healthcare providers emphasized oncological outcomes as tumour recurrence, risk of an ostomy and poor bowel function. Patients perceived absolute risks of adverse outcome to be lower than healthcare providers and were quite willing undergo organ preservation to achieve a better prospect of quality of life. Conclusion: Patients’ preferences in treatment of early rectal cancer vary between patients and frequently differ from assumptions of preferences by healthcare providers. To optimize future shared decision-making, healthcare providers should be aware of these differences and should invite patients to explore and address their priorities more explicitly during consultation. Factors deemed important by both physicians and patients should be expressed during consultation to decide on a tailored treatment strategy

Developing effective and resilient human-agent teamwork using team design patterns

Human-agent teams exhibit emergent behavior at the team level, as a result of interactions between individuals within the team. This begs the question how to design artificial team members (agents) as adequate team players that contribute to the team processes advancing team performance, resilience and learning. This paper proposes the development of a library of Team Design Patterns as a way to make dynamic team behavior at the team and individual level more explicit. Team Design Patterns serve a dual purpose: (1) In the system development phase, designers can identify desirable team patterns for the creation of artificial team members. (2) During the operational phase, team design patterns can be used by artificial team members to drive and stimulate team development, and to adaptively mitigate problems that may arise. We describe a pattern language for specifying team design patterns, discuss their use, and illustrate the concept using representative human-agent teamwork applications