Finding the limits of single-track deposition experiments: An experimental study of melt pool characterization in laser powder bed fusion

Autor: Frieden Templeton William, Hinnebusch Shawn, Strayer Seth, To Albert, Narra Sneha Prabha

Publikováno v: Materials & Design, Vol 231, Iss , Pp 112069- (2023)

This work identifies sources of error in melt pool characterization tests that are frequently employed to study processing parameters in laser powder bed fusion (L-PBF) additive manufacturing (AM). At an early stage in process parameter development,

Externí odkaz: https://doaj.org/article/639d7c95b0cf4aaea3ae5568c3451ec7

EarthGen: Generating the World from Top-Down Views

Autor: Sharma, Ansh, Xiao, Albert, Rathi, Praneet, Kundu, Rohit, Zhai, Albert, Shen, Yuan, Wang, Shenlong

In this work, we present a novel method for extensive multi-scale generative terrain modeling. At the core of our model is a cascade of superresolution diffusion models that can be combined to produce consistent images across multiple resolutions. Pa

Externí odkaz: http://arxiv.org/abs/2409.01491

gSeaGen code by KM3NeT: an efficient tool to propagate muons simulated with CORSIKA

Autor: Aiello, S., Albert, A., Alhebsi, A. R., Alshamsi, M., Garre, S. Alves, Ambrosone, A., Ameli, F., Andre, M., Androutsou, E., Aphecetche, L., Ardid, M., Ardid, S., Atmani, H., Aublin, J., Badaracco, F., Bailly-Salins, L., Bardačová, Z., Baret, B., Bariego-Quintana, A., Becherini, Y., Bendahman, M., Benfenati, F., Benhassi, M., Bennani, M., Benoit, D. M., Berbee, E., Bertin, V., Beyer, C., Biagi, S., Boettcher, M., Bonanno, D., Bouasla, A. B., Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Bozza, R. M., Brânzaş, H., Bretaudeau, F., Breuhaus, M., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Capone, A., Carenini, F., Carretero, V., Cartraud, T., Castaldi, P., Cecchini, V., Celli, S., Cerisy, L., Chabab, M., Chadolias, M., Chen, A., Cherubini, S., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Condorelli, A., Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., Dallier, R., Darras, Y., De Benedittis, A., De Martino, B., De Wasseige, G., Decoene, V., Del Rosso, I., Di Mauro, L. S., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Drakopoulou, E., Drouhin, D., Ducoin, J. -G., Dvornický, R., Eberl, T., Eckerová, E., Eddymaoui, A., van Eeden, T., Eff, M., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Ellajosyula, V., Enzenhöfer, A., Ferrara, G., Filipović, M. D., Filippini, F., Franciotti, D., Fusco, L. A., Gagliardini, S., Gal, T., Méndez, J. García, Soto, A. Garcia, Oliver, C. Gatius, Geißelbrecht, N., Genton, E., Ghaddari, H., Gialanella, L., Gibson, B. K., Giorgio, E., Goos, I., Goswami, P., Gozzini, S. R., Gracia, R., Guidi, C., Guillon, B., Gutiérrez, M., Haack, C., van Haren, H., Hassieiev, V., Heijboer, A., Hennig, L., Hernández-Rey, J. J., Ibnsalih, W. Idrissi, Illuminati, G., Joly, D., de Jong, M., de Jong, P., Jung, B. J., Kalaczyński, P., Kistauri, G., Kopper, C., Kouchner, A., Kueviakoe, V., Kulikovskiy, V., Kvatadze, R., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Lazo, A., Stum, S. Le, Lehaut, G., Lemaître, V., Leonora, E., Lessing, N., Levi, G., Clark, M. Lindsey, Longhitano, F., Magnani, F., Majumdar, J., Malerba, L., Mamedov, F., Manfreda, A., Marconi, M., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Mastrodicasa, M., Mastroianni, S., Mauro, J., Miele, G., Migliozzi, P., Migneco, E., Mitsou, M. L., Mollo, C. M., Morales-Gallegos, L., Moretti, G., Moussa, A., Mateo, I. Mozun, Muller, R., Musone, M. R., Musumeci, M., Navas, S., Nayerhoda, A., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, Oliviero, V., Orlando, A., Oukacha, E., Paesani, D., González, J. Palacios, Papalashvili, G., Parisi, V., Gomez, E. J. Pastor, Păun, A. M., Păvălaş, G. E., Pelegris, I., Martínez, S. Peña, Perrin-Terrin, M., Pestel, V., Pestes, R., Piattelli, P., Poirè, C., Popa, V., Pradier, T., Prado, J., Pulvirenti, S., Quiroz-Rangel, C. A., Rahaman, U., Randazzo, N., Razzaque, S., Rea, I. C., Real, D., Riccobene, G., Robinson, J., Romanov, A., Šaina, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanfilippo, S., Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schumann, J., Schutte, H. M., Seneca, J., Sennan, N., Setter, B., Sgura, I., Shanidze, R., Sharma, A., Shitov, Y., Šimkovic, F., Simonelli, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Štekl, I., Taiuti, M., Tayalati, Y., Thiersen, H., Thoudam, S., de la Torre, P., Melo, I. Tosta e, Tragia, E., Trocmé, B., Tsourapis, V., Tudorache, A., Tzamariudaki, E., Ukleja, A., Vacheret, A., Valsecchi, V., Van Elewyck, V., Vannoye, G., Vasileiadis, G., de Sola, F. Vazquez, Veutro, A., Viola, S., Vivolo, D., van Vliet, A., Warnhofer, H., Weissbrod, S., de Wolf, E., Lhenry-Yvon, I., Zarpapis, G., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., Zywucka, N.

The KM3NeT Collaboration has tackled a common challenge faced by the astroparticle physics community, namely adapting the experiment-specific simulation software to work with the CORSIKA air shower simulation output. The proposed solution is an exten

Externí odkaz: http://arxiv.org/abs/2410.24115

Get a Grip: Multi-Finger Grasp Evaluation at Scale Enables Robust Sim-to-Real Transfer

Autor: Lum, Tyler Ga Wei, Li, Albert H., Culbertson, Preston, Srinivasan, Krishnan, Ames, Aaron D., Schwager, Mac, Bohg, Jeannette

This work explores conditions under which multi-finger grasping algorithms can attain robust sim-to-real transfer. While numerous large datasets facilitate learning generative models for multi-finger grasping at scale, reliable real-world dexterous g

Externí odkaz: http://arxiv.org/abs/2410.23701

End-to-End Ontology Learning with Large Language Models

Autor: Lo, Andy, Jiang, Albert Q., Li, Wenda, Jamnik, Mateja

Ontologies are useful for automatic machine processing of domain knowledge as they represent it in a structured format. Yet, constructing ontologies requires substantial manual effort. To automate part of this process, large language models (LLMs) ha

Externí odkaz: http://arxiv.org/abs/2410.23584