A Unified Framework for Parallel Anisotropic Mesh Adaptation

Finite-element methods are a critical component of the design and analysis procedures of many (bio-)engineering applications. Mesh adaptation is one of the most crucial components since it discretizes the physics of the application at a relatively low cost to the solver. Highly scalable parallel mesh adaptation methods for High-Performance Computing (HPC) are essential to meet the ever-growing demand for higher fidelity simulations. Moreover, the continuous growth of the complexity of the HPC systems requires a systematic approach to exploit their full potential. Anisotropic mesh adaptation captures features of the solution at multiple scales while, minimizing the required number of elements. However, it also introduces new challenges on top of mesh generation. Also, the increased complexity of the targeted cases requires departing from traditional surface-constrained approaches to utilizing CAD (Computer-Aided Design) kernels. Alongside the functionality requirements, is the need of taking advantage of the ubiquitous multi-core machines. More importantly, the parallel implementation needs to handle the ever-increasing complexity of the mesh adaptation code. In this work, we develop a parallel mesh adaptation method that utilizes a metric-based approach for generating anisotropic meshes. Moreover, we enhance our method by interfacing with a CAD kernel, thus enabling its use on complex geometries. We evaluate our method both with fixed-resolution benchmarks and within a simulation pipeline, where the resolution of the discretization increases incrementally. With the Telescopic Approach for scalable mesh generation as a guide, we propose a parallel method at the node (multi-core) for mesh adaptation that is expected to scale up efficiently to the upcoming exascale machines. To facilitate an effective implementation, we introduce an abstract layer between the application and the runtime system that enables the use of task-based parallelism for concurrent mesh operations. Our evaluation indicates results comparable to state-of-the-art methods for fixed-resolution meshes both in terms of performance and quality. The integration with an adaptive pipeline offers promising results for the capability of the proposed method to function as part of an adaptive simulation. Moreover, our abstract tasking layer allows the separation of different aspects of the implementation without any impact on the functionality of the method

Parallel Anisotropic Unstructured Grid Adaptation

Computational Fluid Dynamics (CFD) has become critical to the design and analysis of aerospace vehicles. Parallel grid adaptation that resolves multiple scales with anisotropy is identified as one of the challenges in the CFD Vision 2030 Study to increase the capacity and capability of CFD simulation. The Study also cautions that computer architectures are undergoing a radical change and dramatic increases in algorithm concurrency will be required to exploit full performance. This paper reviews four different methods to parallel anisotropic grid generation. They cover both ends of the spectrum: (i) using existing state-of-the-art software optimized for a single core and modifying it for parallel platforms and (ii) designing and implementing scalable software with incomplete, but rapidly maturating functionality. A brief overview for each grid adaptation system is presented in the context of a telescopic approach for multilevel concurrency. These methods employ different approaches to enable parallel execution, which provides a unique opportunity to illustrate the relative behavior of each approach. Qualitative and quantitative metric evaluations are used to draw lessons for future developments in this critical area for parallel CFD simulation

Extreme-Scale Parallel Mesh Generation: Telescopic Approach

In this poster we focus and present our preliminary results pertinent to the integration of multiple parallel Delaunay mesh generation methods into a coherent hierarchical framework. The goal of this project is to study our telescopic approach and to develop Delaunay-based methods to explore concurrency at all hardware layers using abstractions at (a) medium-grain level for many cores within a single chip and (b) coarse-grain level, i.e., sub-domain level using proper error metric- and application-specific continuous decomposition methods

Ανάλυση συνεχούς λόγου σε διαλογικά περιβάλλοντα διδασκαλίας λογοτεχνίας με τη μέθοδο του ερμηνευτικού διαλόγου

Η παρούσα έρευνα αποσκοπεί στην μελέτη του ερμηνευτικού διαλόγου μέσα από το πρίσμα συγκεκριμένων διαλογικών επεισοδίων, όπως αναπτύχθηκαν στο μάθημα της λογοτεχνίας. Συγκεκριμένα, διερευνά τον ερμηνευτικό διάλογο ως σχολική αναγνωστική πρακτική στο πλαίσιο της λογοτεχνικής εκπαίδευσης, εστιάζοντας την προσοχή στον τρόπο με τον οποίο οι λεκτικές αλληλεπιδράσεις καθηγητή και μαθητών τον αναδεικνύουν. Με βάση τις θεωρητικές αρχές και διαδικασίες που ορίζει η μεθοδολογική προσέγγιση της ανάλυσης συνεχούς λόγου (discourse analysis), σχηματίστηκε μία βάση δεδομένων που αποτελούνταν από διαδοχικά εκφωνήματα του καθηγητή και μαθητών, έτσι όπως παρατηρήθηκαν στις διδασκαλίες λογοτεχνίας σε συνθήκες ερμηνευτικού διαλόγου στην τάξη του συνεργαζόμενου Λυκείου των Αθηνών. Η ανάλυση των δεδομένων πραγματοποιήθηκε σε δύο επίπεδα: Στο πρώτο επίπεδο, ο κύριος ερευνητικός στόχος αφορούσε την αναγνώριση και κατηγοριοποίηση της μορφής των εκφωνημάτων και ο προσδιορισμός του αντίκτυπού τους στην πορεία των μετέπειτα λεκτικών αλληλεπιδράσεων ώστε να αναδειχθούν μοτίβα και στρατηγικές οικοδόμησης σημασίας. Στο δεύτερο επίπεδο κύριος ερευνητικός στόχος αφορά την εξερεύνηση του πλαισίου το οποίο περιστοιχίζει τα εκφωνήματα, εστιάζοντας στο περιεχόμενο του εκφωνήματος. Γίνεται προσπάθεια να αναδειχθεί ο τρόπος με τον οποίο το περιεχόμενο του εκφωνήματος αλληλεπιδρά με το δεδομένο πλαίσιο της διαλογικής αλληλεπίδρασης και με τα μετέπειτα εκφωνήματα, σύμφωνα με την έννοια της διαδοχικής οργάνωσης των εκφωνημάτων. Η ανάλυση των δεδομένων αναδεικνύει πως, κατά την εφαρμογή του ερμηνευτικού διαλόγου, η διαλογική αλληλεπίδραση είναι υψίστης σημασίας στις διαδικασίες οικοδόμησης σημασίας και ερμηνείας του λογοτεχνικού κειμένου. Συμπερασματικά, οι γλωσσικές αποτυπώσεις που παρατηρήθηκαν, ειδικά μεταξύ των μαθητών, παρουσιάζουν υψηλούς δείκτες αλληλεξάρτησης· μέσω του διαλόγου η ερμηνευτική θέση του μαθητή συν-οικοδομείται.This research aims to explore the practice of hermeneutic dialogue through the lens of specific dialogue instances taking place in literature teaching scenarios. More specifically, it explores the hermeneutic dialogue as a reading practice within this framework, focusing on the ways in which verbal interactions promote its various aspects. According to the methodological principles and processes of discourse analysis, sequential utterances between students and teacher from literature classes at the collaborating high school of Athens were collected into a database. The analysis of the data took place in two steps. In the first step, the main research goal was the recognition and categorization of the forms of the utterances and the exploration of their impact in future verbal interactions, highlighting motifs and strategies in the process of meaning construction. In the next step, the main goal was the exploration of the contexts in which the utterances take place, with a focus on the content of the utterances. More specifically, an effort was made to highlight the ways in which the content of the utterance interacts with the given context and with subsequent utterances, in line with the concept of the sequential organization of utterances. Data analysis suggests that, through the lens of hermeneutic dialogue principles, these dialogue interactions play a major role in meaning construction and interpretation of literary subjects. In conclusion, significant interdependence between utterances, especially student to student utterances, was observed; the students’ interpretive positions are co-constructed through dialogue

Parallel Anisotropic Unstructured Grid Adaptation

Computational fluid dynamics (CFD) has become critical to the design and analysis of aerospace vehicles. Parallel grid adaptation that resolves multiple scales with anisotropy is identified as one of the challenges in the CFD Vision 2030 Study to increase the capacity and capability of CFD simulation. The study also cautions that computer architectures are undergoing a radical change, and dramatic increases in algorithm concurrency will be required to exploit full performance. This paper reviews four different methods to parallel anisotropic grid adaptation. They cover both ends of the spectrum: 1) using existing state-of-the-art software optimized for a single core and modifying it for parallel platforms, and 2) designing and implementing scalable software with incomplete but rapidly maturing functionality. A brief overview for each grid adaptation system is presented in the context of a telescopic approach for multilevel concurrency. These methods employ different approaches to enable parallel execution, which provides a unique opportunity to illustrate the relative behavior of each approach. Qualitative and quantitative metric evaluations are used to draw lessons for future developments in this critical area for parallel CFD simulation

Wine Traceability with Rare Earth Elements

The traceability of foodstuffs is now a relevant aspect of the food market. Scientific research has been devoted to addressing this issue by developing analytical protocols in order to find the link between soil and food items. In this view, chemical parameters that can act as soil markers are being sought. In this work, the role of rare earth elements (REEs) as geochemical markers in the traceability of red wine is discussed. The REE distribution in samples from each step of the wine making process of Primitivo wine (produced in Southern Italy) was determined using the highly sensitive inductively coupled plasma-mass spectrometry (ICP-MS) technique. Samples analyzed include grapes, must, and wine samples after every step in the vinification process. The resulting data were compared to the REE distribution in the soil, revealing that the soil fingerprint is maintained in the intermediate products up to and including grape must. Fractionation occurs thereafter as a consequence of further external interventions, which tends to modify the REE profile

Authentication and traceability study on barbera d\u2019asti and nizza docg wines: The role of trace-and ultra-trace elements

Barbera d\u2019Asti\u2014including Barbera d\u2019Asti superiore\u2014and Nizza are two DOCG (Denominazione di Origine Controllata e Garantita) wines produced in Piemonte (Italy) from the Barbera grape variety. Differences among them arise in the production specifications in terms of purity, ageing, and zone of production, in particular with concern to Nizza, which follows the most stringent rules, sells at three times the average price, and is considered to have the highest market value. To guarantee producers and consumers, authentication methods must be developed in order to distinguish among the different wines. As the production zones totally overlap, it is important to verify whether the distinction is possible or not according to metals content, or whether chemical markers more linked to winemaking are needed. In this work, Inductively Coupled Plasma (ICP) elemental analysis and multivariate data analysis are used to study the authentication and traceability of samples from the three designations of 2015 vintage. The results show that, as far as elemental distribution in wine is concerned, work in the cellar, rather than geographic provenance, is crucial for the possibility of distinction

Antioxidant Composition of a Selection of Italian Red Wines and Their Corresponding Free-Radical Scavenging Ability

This study correlates the antioxidant composition profiles and the overall antioxidant capacities of 36 Italian red wine samples. The samples were fully characterized by chromatographic and spectrophotometric techniques. The overall antioxidant capacity was determined by titrating a solution of the semistable free radical DPPH (1,1-diphenyl-2-picrylhydrazyl) with each wine sample followed by Electron Paramagnetic Resonance (EPR) spectroscopy and then measuring the resulting decrease in DPPH-signal. The antioxidant activities of the samples were expressed as (+)-catechin equivalents and related to their antioxidant composition profiles. Samples with a high polyphenol content showed a high DPPH scavenging ability as well. Seven well-defined groups, mainly constituted by wines coming from the same cultivar, were evidenced by PCA analysis. Alcohol content and pH did not influence the wine DPPH scavenging ability. The most important variables contributing to the wines’ antioxidant power are total flavonoid, total phenol, and proanthocyanidin indices together with fertaric acid, trans-caftaric acid, trans-coutaric acid, and both quercetin glucoside and quercetin glucuronide. EPR is demonstrated to be faster than the other analytical methods (spectrophotometric and chromatographic analyses) to determine the wine overall antioxidant activity

Adaptive Physics-Based Non-Rigid Registration for Immersive Image-Guided Neuronavigation Systems

Objective: In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, particularly in the presence of tumor resection. Non-Rigid Registration (NRR) of the preoperative image data can be used to create a registered image that captures the deformation in the intraoperative image while maintaining the quality of the preoperative image. Using clinical data, this paper reports the results of a comparison of the accuracy and performance among several non-rigid registration methods for handling brain deformation. A new adaptive method that automatically removes mesh elements in the area of the resected tumor, thereby handling deformation in the presence of resection is presented. To improve the user experience, we also present a new way of using mixed reality with ultrasound, MRI, and CT. Materials and methods: This study focuses on 30 glioma surgeries performed at two different hospitals, many of which involved the resection of significant tumor volumes. An Adaptive Physics-Based Non-Rigid Registration method (A-PBNRR) registers preoperative and intraoperative MRI for each patient. The results are compared with three other readily available registration methods: a rigid registration implemented in 3D Slicer v4.4.0; a B-Spline non-rigid registration implemented in 3D Slicer v4.4.0; and PBNRR implemented in ITKv4.7.0, upon which A-PBNRR was based. Three measures were employed to facilitate a comprehensive evaluation of the registration accuracy: (i) visual assessment, (ii) a Hausdorff Distance-based metric, and (iii) a landmark-based approach using anatomical points identified by a neurosurgeon. Results: The A-PBNRR using multi-tissue mesh adaptation improved the accuracy of deformable registration by more than five times compared to rigid and traditional physics based non-rigid registration, and four times compared to B-Spline interpolation methods which are part of ITK and 3D Slicer. Performance analysis showed that A-PBNRR could be applied, on average, in \u3c2 min, achieving desirable speed for use in a clinical setting. Conclusions: The A-PBNRR method performed significantly better than other readily available registration methods at modeling deformation in the presence of resection. Both the registration accuracy and performance proved sufficient to be of clinical value in the operating room. A-PBNRR, coupled with the mixed reality system, presents a powerful and affordable solution compared to current neuronavigation systems

Comparison of Physics-Based Deformable Registration Methods for Image-Guided Neurosurgery

This paper compares three finite element-based methods used in a physics-based non-rigid registration approach and reports on the progress made over the last 15 years. Large brain shifts caused by brain tumor removal affect registration accuracy by creating point and element outliers. A combination of approximation- and geometry-based point and element outlier rejection improves the rigid registration error by 2.5 mm and meets the real-time constraints (4 min). In addition, the paper raises several questions and presents two open problems for the robust estimation and improvement of registration error in the presence of outliers due to sparse, noisy, and incomplete data. It concludes with preliminary results on leveraging Quantum Computing, a promising new technology for computationally intensive problems like Feature Detection and Block Matching in addition to finite element solver; all three account for 75% of computing time in deformable registration