Modeling the bond strength in overmolded thermoplastic composite structures

Ressourceneffizienter Leichtbau ermöglicht die Entwicklung und Herstellung technischer Lösungen und Produkte mit einem minimalen Material- und Energieeinsatz bei gleichzeitig maximalem Wirkungsgrad. Insbesondere in der Mobilitätsbranche ist die Reduktion bewegter Massen eine geeignete Maßnahme zur Effizienzsteigerung. Für Mobilitätsanwendungen mit hohen Stückzahlen haben sich als Leichtbauwerkstoffe neben konventionellen Leichtmetallen insbesondere thermoplastische Kunststoffe und Verbundwerkstoffe etabliert. Als innovatives Fertigungsverfahren zur Herstellung strukturell leistungsfähiger und gleichzeitig hoch funktionsintegrierter Bauteile, wurde im vergangenen Jahrzehnt das Hinterspritzverfahren entwickelt. Es vereint die Vorteile etablierter Spritzgießprozesse mit den hervorragenden mechanischen Eigenschaften endlosfaserverstärkter Halbzeuge. Realisiert wird dies durch die Integration thermoplastischer Faser-Kunststoff-Verbunde (TP-FKV) in den Spritzgießprozess und die direkte Ausbildung einer festen Verbindung durch das Überströmen mit Polymerschmelze, wobei die thermoplastischen Materialsysteme interdiffundieren. Die Sicherstellung einer hinreichenden Verbundfestigkeit zwischen TP-FKV und spritzgegossener Struktur stellt ein maßgebliches Auslegungskriterium für hinterspritzte thermoplastische Faserverbundstrukturen dar. Im Rahmen der vorliegenden Arbeit wird die Ausbildung der Verbundfestigkeit während des Hinterspritzprozesses eingehend ergründet, um darauf aufbauend ein geeignetes Modell sowie eine Auslegungsmethodik für die virtuelle Vorhersage der Verbundfestigkeit aufzustellen. Hierfür wird die Phänomenologie des Hinterspritzprozesses und der Festigkeitsevolution zunächst anhand von vereinfachten Prüfgeometrien untersucht und die Einflüsse der Prozessparameter und der jeweiligen Materialspezifikationen analysiert. Die somit ermittelten Abhängigkeiten zwischen den Prozessgrößen des Hinterspritzverfahrens und der Verbundfestigkeit dienen als Validierungsdaten für die anschließende Modellentwicklung. Dazu werden die relevanten material- und prozessspezifischen Effekte abstrahiert und in eine analytische Berechnungsvorschrift überführt. Durch die Beschreibung und Berechnung der Kontaktbedingungen und des Verschmelzungsprozesses im Grenzbereich kann die Verbundfestigkeit lokal evaluiert werden. Die notwendigen Eingangsgrößen des entwickelten Modells werden durch die numerische Simulation des Hinterspritzprozesses ermittelt, wodurch der Grenzschichtzustand orts- und zeitaufgelöst evaluiert werden kann. Zusätzlich liefert die Simulation des Thermoformprozesses des faserverstärkten Halbzeugs Informationen über die vor dem Hinterspritzen vorliegenden Oberflächenzustände, welche in der Modellvorschrift berücksichtigt werden können. Anhand eines Demonstrationsszenarios wird die Modellierungs- und Berechnungsmethodik vollständig durchgeführt, um die Verbundfestigkeitsverteilung in der Grenzschicht für eine anwendungsnahe Struktur vorherzusagen. Auf diese Weise wird das Transferpotenzial dieser Arbeit aufgezeigt.Resource-efficient lightweight engineering enables the development and manufacturing of technical solutions and products with minimal consumption of materials and energy whilst achieving maximum efficiency. Reducing moving masses is a suitable approach to increase efficiency, particularly in the mobility sector. In addition to conventional light metals, thermoplastics and composite materials have established as lightweight materials for high-volume mobility applications. As an innovative manufacturing process for the production of high-performing yet highly functionally integrated components, the overmolding process has been developed during the past decade. It combines the advantages of established injection molding processes with the outstanding mechanical properties of continuous fiber-reinforced semi-finished products. This is achieved by integrating thermoplastic fiber-reinforced composites (TP-FRC) into the injection molding process and directly establishing a solid bond by overflowing with polymer melt, whereby the thermoplastic material systems interdiffuse. Ensuring sufficient bond strength between TP-FRC and the injection-molded structure is a key design criterion for overmolded thermoplastic composite structures. Within the scope of this thesis, the formation of the bond strength during the overmolding process is investigated in detail in order to develop a suitable model as well as a design methodology for the virtual prediction of the bond strength. Therefore, the phenomenology of the overmolding process and the strength evolution is first examined using simplified test geometries from which the influences of the process parameters and the particular material specifications are analyzed. The resulting dependencies between the process variables of the overmolding process and the bond strength serve as validation data for the subsequent model development. For this purpose, the relevant material and process-specific effects are abstracted and transferred into an analytical calculation formula. By describing and computing the contact conditions and the fusion process in the interface area, the bond strength can be evaluated locally. The necessary input variables for the developed model are determined by means of numerical simulation of the overmolding process, whereby the interface state can be evaluated with spatial and time resolution. In addition, the simulation of the thermoforming process of the fiber-reinforced semi-finished product provides information about the surface conditions present before overmolding, which can be taken into account in the model specifications. A demonstration scenario is used to fully implement the modeling and computation methodology to predict the bond strength distribution in the interface for an application-oriented structure. Thus, the transfer potential of this thesis is presented

Simulation-based digital twin for the manufacturing of thermoplastic composites

The bond strength between a thermoformed fibre reinforced thermoplastic sheet and an injected polymer is the limiting factor for the structural integrity of overmoulded thermoplastic composites. In this contribution, a simulation based digital twin of the thermoforming process is presented. From numerical parametric studies a reduced order model based on Proper Orthogonal Decomposition (POD) is developed. The combination with machine learning methods enables the real-time computation of arbitrary physical reliable temperature fields with sufficient accuracy to be used for design purposes and as inline quality gates

Numerical Modelling of Bond Strength in Overmoulded Thermoplastic Composites

Overmoulding of thermoplastic composites combines the steps of thermoforming and injection moulding in an integrated manufacturing process. The combination of continuous fibre-reinforced thermoplastics with overmoulded polymer enables the manufacturing of highly func-tionally integrated structures with excellent mechanical properties. When performed as a one-shot process, an economically efficient manufacturing of geometrical complex lightweight parts within short cycle times is possible. However, a major challenge in the part and process design of over-moulded thermoplastic composites (OTC) is the assurance of sufficient bond strength between the composite and the overmoulded polymers. Within the framework of a simulation-based approach, this study aims to develop a methodology for predicting the bond strength in OTC using simulation data and a numerical model formulation of the bonding mechanisms. Therefore, a modelling approach for the determination of the bond strength depending on different process parameters is presented. In order to validate the bond strength model, specimens are manufactured with different process settings and mechanical tests are carried out. Overall, the results of the numerical computation are in good agreement with the experimentally determined bond strength. The proposed modelling approach enables the prediction of the local bond strength in OTC, considering the interface conditions and the processing history

Integrated computational product and production engineering for multi-material lightweight structures

Within product development processes, computational models are used with increasing frequency. However, the use of those methods is often restricted to the area of focus, where product design, manufacturing process, and process chain simulations are regarded independently. In the use case of multi-material lightweight structures, the desired products have to meet several requirements regarding structural performance, weight, costs, and environment. Hence, manufacturing-related effects on the product as well as on costs and environment have to be considered in very early phases of the product development process in order to provide a computational concept that supports concurrent engineering. In this contribution, we present an integrated computational concept that includes product engineering and production engineering. In a multi-scale framework, it combines detailed finite element analyses of products and their related production process with process chain and factory simulations. Including surrogate models based on machine learning, a fast evaluation of production impacts and requirements can be realized. The proposed integrated computational product and production engineering concept is demonstrated in a use case study on the manufacturing of a multi-material structure. Within this study, a sheet metal forming process in combination with an injection molding process of short fiber reinforced plastics is investigated. Different sets of process parameters are evaluated virtually in terms of resulting structural properties, cycle times, and environmental impacts. © 2020, The Author(s)

The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics.

ABSTRACT: A global genome database of all of Earth’s species diversity could be a treasure trove of scientific discoveries. However, regardless of the major advances in genome sequencing technologies, only a tiny fraction of species have genomic information available. To contribute to a more complete planetary genomic database, scientists and institutions across the world have united under the Earth BioGenome Project (EBP), which plans to sequence and assemble high-quality reference genomes for all ∼1.5 million recognized eukaryotic species through a stepwise phased approach. As the initiative transitions into Phase II, where 150,000 species are to be sequenced in just four years, worldwide participation in the project will be fundamental to success. As the European node of the EBP, the European Reference Genome Atlas (ERGA) seeks to implement a new decentralised, accessible, equitable and inclusive model for producing high-quality reference genomes, which will inform EBP as it scales. To embark on this mission, ERGA launched a Pilot Project to establish a network across Europe to develop and test the first infrastructure of its kind for the coordinated and distributed reference genome production on 98 European eukaryotic species from sample providers across 33 European countries. Here we outline the process and challenges faced during the development of a pilot infrastructure for the production of reference genome resources, and explore the effectiveness of this approach in terms of high-quality reference genome production, considering also equity and inclusion. The outcomes and lessons learned during this pilot provide a solid foundation for ERGA while offering key learnings to other transnational and national genomic resource projects.info:eu-repo/semantics/publishedVersio

The European Reference Genome Atlas: piloting a decentralised approach to equitable biodiversity genomics

A genomic database of all Earth’s eukaryotic species could contribute to many scientific discoveries; however, only a tiny fraction of species have genomic information available. In 2018, scientists across the world united under the Earth BioGenome Project (EBP), aiming to produce a database of high-quality reference genomes containing all ~1.5 million recognized eukaryotic species. As the European node of the EBP, the European Reference Genome Atlas (ERGA) sought to implement a new decentralised, equitable and inclusive model for producing reference genomes. For this, ERGA launched a Pilot Project establishing the first distributed reference genome production infrastructure and testing it on 98 eukaryotic species from 33 European countries. Here we outline the infrastructure and explore its effectiveness for scaling high-quality reference genome production, whilst considering equity and inclusion. The outcomes and lessons learned provide a solid foundation for ERGA while offering key learnings to other transnational, national genomic resource projects and the EBP.info:eu-repo/semantics/publishedVersio

Sex differences in oncogenic mutational processes.

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts