Computation of Fiber Orientation in X-Ray Micro-Tomography Reconstructions

No abstract availabl

Microscale Analysis of Spacecraft Heat Shields

Imagine entering Earths atmosphere after returning from the outer solar system. A heat shield less than 2 inches thick protects you from temperatures up to 2,900 Celsius (5,252 Fahrenheit). Such conditions were experienced by NASAs Stardust capsule during reentry in 2006. The only materials capable of providing the necessary protection are composites with complex microstructures. Evaluating these materials is difficult, requiring precise knowledge of their properties. To this end, NASA scientists are developing research codes to compute material properties and simulate ablation at the microscale using agency supercomputers. Utilizing these tools, along with experiments, researchers are working to push the limits of spaceflight, allowing for greater flexibility in future space missions

Microscale Modeling of High-Temperature Heat Transfer in Anisotropic Porous Materials

No abstract availabl

An empirical study of entrepreneurial passion in the crowdfunding context : an equity crowdfunding focus and a cross-industry perspective

LAUREA MAGISTRALEIl finanziamento di una nuova impresa potrebbe essere sostenuto da diversi tipi di investitori e tutti loro possono essere influenzati differentemente da alcune caratteristiche intrinseche dell'imprenditore che vengono mostrate durante la presentazione del pitch. Partendo dalle evidenze di Chen et al. (2009) che analizzano la percezione dell'influenza della passione imprenditoriale sulla decisione di investimento dei VC, e utilizzando le scale di valutazione della passione e della preparazione di Chen, gli autori indagano come la passione e la preparazione mostrate dagli imprenditori possano influenzare la decisione di finanziamento nel contesto del crowdfunding. Viene effettuato un approfondimento sui diversi modelli di crowdfunding con successiva attenzione sui singoli reward-based e equity crowdfunding, ed allo stesso tempo un'ulteriore analisi di come la passione e la preparazione possano influenzare la decisione di finanziamento per diversi settori. La scelta dei due modelli è guidata dalla recente crescente attenzione data all'equity crowdfunding, come spiegato da Lukkarinen et al. (2016), e dalla tendenza generale, diffusasi rapidamente, sulla crescita del crowdfunding come modello di finanziamento. Questo studio porta nuovi contributi soprattutto per gli imprenditori che cercano finanziamenti su una piattaforma di crowdfunding. Utilizzando un campione di 300 progetti svolti tra il 2016 e il 2018, prelevati sia da Crowdcube e Seedrs (per l’equity crowdfunding) che da Kickstarter (per il reward-based crowdfunding), la ricerca evidenzia che la passione ha sempre un effetto positivo sul successo della campagna nei diversi contesti analizzati e, più precisamente, la passione ha un impatto maggiore sul successo della campagna quando si tratta del modello reward-based e quando la preparazione è alta per le campagne di equity crowdfunding. D'altra parte, anche se la preparazione non è statisticamente rilevante da sola per il successo, essa rappresenta un prerequisito per il modello di equity crowdfunding: in sua assenza, anche per alti livelli di passione, l'investitore è restio a finanziare il progetto.Funding of new venture might be sustained by different types of investors and all of them can be influenced in various ways by intrinsic characteristics of the entrepreneur which are shown during the pitch presentation. Starting from the evidence of Chen et al. (2009), analyzing the perception of entrepreneurial passion influence on VCs’ investment decision, and using Chen’s passion and preparedness’ scale valuation, the authors investigate how passion and preparedness displayed by the entrepreneurs might influence the funding decision in the context of crowdfunding. A deep dive on the different crowdfunding models is carried out with a subsequent focus on reward-based and equity-based crowdfunding, as well as a further analysis of how passion and preparedness can affect the funding decision across different industries. The focus on crowdfunding is driven by the recent increasing attention towards equity crowdfunding models, as carefully explained by Lukkarinen et al. (2016), and by the general trend on the increasing diffusion of crowdfunding as a funding model spreading quickly. This study brings new insights especially for entrepreneurs seeking funds from a crowdfunding platform. Using a sample of 300 crowdfunding campaigns held between 2016 and 2018, on Crowdcube and Seedrs (for equity crowdfunding) and Kickstarter (for reward-based crowdfunding), the research finds that passion always has a positive effect on the campaign success in the different contexts analyzed, and more specifically, passion has a stronger effect on crowdfunding success in the reward-based context as well as when preparedness is high in the equity crowdfunding model. On the other hand, even though preparedness is not statistically relevant per sé for success, it represents a pre-requirement in the equity crowdfunding model: if it is not displayed, even for high levels of passion, the investors are less willing to finance the project

arcjetCV: an open-source software to analyze material ablation

arcjetCV is an open-source Python software designed to automate time-resolved measurements of heatshield material recession and recession rates from arcjet test video footage. This new automated and accessible capability greatly exceeds previous manual extraction methods, enabling rapid and detailed characterization of material recession for any sample with a profile video. arcjetCV automates the video segmentation process using machine learning models, including a one-dimensional (1D) Convolutional Neural Network (CNN) to infer the time-window of interest, a two-dimensional (2D) CNN for image and edge segmentation, and a Local Outlier Factor (LOF) for outlier filtering. A graphical user interface (GUI) simplifies the user experience and an application programming interface (API) allows users to call the core functions from scripts, enabling video batch processing. arcjetCV's capability to measure time-resolved recession in turn enables characterization of non-linear processes (shrinkage, swelling, melt flows, etc.), contributing to higher fidelity validation and improved modeling of heatshield material performance. The source code associated with this article can be found at https://github.com/magnus-haw/arcjetCV

Korelacija med plimovanjem severnega dela Jadranskega morja in hidrodinamiko kraškega vodonosnika v jami Pozzo dei Protei di Monfalcone (matični kras)

The Pozzo dei Protei di Monfalcone (northeast Italy) is a cavity developed in Cretaceous limestones (Cenomanian-Turonian) situated near the contact of the north-western zone of the Classical Karst with the Lower Plain of the Isonzo/Soča River. At the bottom of the cave is the groundwater at an average altitude of 1.89 m a.s.l. In consideration of the proximity of the cave with the Adriatic Sea, the possible effects of the tides on the karst aquifer were investigated monitoring groundwater level, electrical conductivity (EC, K25) and water temperature using a CTD diver. Groundwater level daily oscillations show a lag of 4–4.5 hours compared to tides. The electrical conductivity variations that can be correlated to tides are 2–5 μS/cm. Excluding that the cave, given the altimetry, is directly affected by the saltwater wedge, the cyclical variations of the EC would derive from the dispersion at the salt water and fresh water interface and from the mobilization of more mineralized water coming from the rock mass. The hypothesis of mixing fresh and salt water and saline fossil waters in the caves of the area has been verified by a general increase in the chloride ion in this area of the karst aquifer compared to the internal areas of Classical Karst.Pozzo dei Protei di Monfalcone (severovzhodna Italija) je jama, razvita v krednih apnencih (cenomanij-turonij) v bližini stika med severozahodnim delom matičnega krasa in spodnjo soško nižino. Na dnu jame je podzemna voda na povprečni višini 1,89 m n. m. Ker je jama v bližini Jadranskega morja, so bili možni vplivi plimovanja na kraški vodonosnik proučevani na podlagi merjenja nivojev, specifične električne prevodnosti (EC, K25) in temperature podzemne vode z uporabo samodejnih merilnikov s shranjevanjem podatkov. Dnevna nihanja nivojev podzemne vode kažejo zaostanek 4–4.5 ure za plimovanjem. S plimovanjem povezane spremembe specifične električne prevodnosti so 2–5 μS/cm. Ker lahko glede na razmerje višin izključimo neposreden vpliv klina morske vode, lahko ciklične spremembe EC razlagamo z disperzijo na stiku slane in sladke vode ter z mobilizacijo bolj mineralizirane vode iz kamninske osnove. Hipoteza mešanja sladke in slane vode in slanih fosilnih vod v jamah tega območja je bila potrjena s splošnim povišanjem koncentracij kloridnega iona v tem delu kraškega vodonosnika v primerjavi z notranjimi deli matičnega krasa

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is a suite of tools for the analysis of porous materials and generation of material microstructures. From microstructural data, often obtained through X-ray microtomography, PuMA can determine a number of effective material properties and perform material response simulations. Version 2.2 includes capabilities for computing volume fractions, porosity, specific surface area, effective thermal and electrical conductivities, and continuum and rarefied diffusive tortuosity. PuMA can also simulate competitive diffusion/reaction processes at the micro-scale, such as surface oxidation. In this poster, recent advancements to the PuMA software are detailed, including the full refactoring of PuMA into v3.0, a new module to compute heat conduction in anisotropic materials, a particle method for simulating molecular beam experiments, a new finite-volume Laplace solver, complex fibrous material generation, woven material generation, and a coupling of PuMA with the DAKOTA software for advanced statistics

NeRF applied to satellite imagery for surface reconstruction

We present Surf-NeRF, a modified implementation of the recently introduced Shadow Neural Radiance Field (S-NeRF) model. This method is able to synthesize novel views from a sparse set of satellite images of a scene, while accounting for the variation in lighting present in the pictures. The trained model can also be used to accurately estimate the surface elevation of the scene, which is often a desirable quantity for satellite observation applications. S-NeRF improves on the standard Neural Radiance Field (NeRF) method by considering the radiance as a function of the albedo and the irradiance. Both these quantities are output by fully connected neural network branches of the model, and the latter is considered as a function of the direct light from the sun and the diffuse color from the sky. The implementations were run on a dataset of satellite images, augmented using a zoom-and-crop technique. A hyperparameter study for NeRF was carried out, leading to intriguing observations on the model's convergence. Finally, both NeRF and S-NeRF were run until 100k epochs in order to fully fit the data and produce their best possible predictions. The code related to this article can be found at https://github.com/fsemerar/surfnerf

Modeling the Effective Thermal Conductivity of Anisotropic Porous Materials

No abstract availabl