Hudbay Minerals (Canada)

Abstract Practitioners increasingly require pre-design modeling capabilities to guide efforts in housing renovations, which can be expensive and time-consuming. In parallel, researchers have advanced building surrogate modeling techniques to reduce simulation time, but little work has been done on models predicting indoor environmental conditions at sub-annual resolutions to support passive design and performance. This work develops the capability to simulate indoor thermal conditions at much higher speeds than traditional workflows. This is achieved through a flexible methodology that transforms physics-based building performance simulation (BPS) models into reduced order surrogate models, utilizing machine learning (ML) techniques as well as dataset generation through parallel computing. The surrogate outputs predict thermal environment measures, such as operative temperature, air temperature, and standard effective temperature. This study applies the workflow to a residential single-family archetype in Canada, achieving accurate predictions with errors lower than 5% CV(RMSE), and very little over- or under-estimation (NMBE lower than 0.06%) at speeds more than six times faster than typical surrogate modelling workflows. This work is significant because it leverages surrogate modeling techniques to predict indoor thermal conditions, supporting design workflows that highlight thermal autonomy, i.e., a building’s ability to passively maintain comfortable conditions for occupants.

Rock hardness and abrasivity are among the most crucial properties that can significantly impact the interaction between rocks and mechanical tools in different parts of geoengineering projects. Accurate estimation of these properties is essential for a better understanding and optimization of geoengineering operations. Hence, the main aim of this study was to develop different machine learning (ML) models based on the geochemical measurements for predicting rock hardness and abrasivity. To do this, 159 rock samples were collected from a gold mine, and portable X-ray fluorescence spectrometry (pXRF), Leeb rebound hardness (LRH), and Cerchar abrasivity index (CAI) tests were performed on the collected rock samples. Three different ML algorithms, including random forest regressor (RFR), support vector regression, and gradient boosting regressor, were applied to develop predictive models for LRH and CAI separately. Considering the fact that the geochemical data are of the compositional type, two scenarios were followed: developing predictive models based on the original data obtained from the pXRF and the centered log-ratio (Clr) transformed data, resulting in the development of six predictive models for LRH and CAI. The performance assessment of the developed predictive models showed that RFR models outperformed the other two ML algorithms in predicting LRH and CAI. In addition, the developed models based on the original data demonstrated a better performance in both cases of LRH and CAI than the trained model based on Clr data. The result indicates that integrated pXRF measurements and RFR technique have strong potential to be used for practical and efficient rock materials characterization during exploration and extraction processes.

Organy administracji geologicznej zajmują się m.in. regulowaniem działalności inwestorów polegającej na poszukiwaniu i rozpoznawaniu złóż kopalin. W praktyce, działania te obejmują wyznaczanie terminów obligatoryjnego rozpoczęcia prac wiertniczych od momentu uzyskania koncesji, a także innych, takich jak czas trwania wiercenia, lub czas wykonania rekultywacji, gdzie udział mają również organy samorządowe. W artykule skonfrontowano wyznaczony przez organkoncesyjny termin wykonywania robót wiertniczych z realnym procesem uzyskania zgód potrzebnych do rozpoczęcia robótwiertniczych. Przedstawione procesy i ich rozwlekłość pokazują absurdalność niektórych wymogów obowiązujących w tejmaterii inwestorów i wykonawców wierceń. Dla obrazowego przedstawienia problemu posłużono się studium przypadku,wykorzystującym przykład jednego otworu wykonywanego w ramach koncesji na poszukiwanie i rozpoznawanie złoża rudmiedzi i srebra w obszarze „Nowa Sól”. W artykule skonfrontowano terminy i przepisy KPA oraz cały szereg prac koniecznychdo realizacji, a także decyzji, opinii i zgód niezbędnych do uzyskania w celu pomyślnego przeprowadzenia całego procesuwiercenia od wyznaczenia lokalizacji do zatwierdzenia zakończenia rekultywacji gruntów.

This paper discusses the physical and mathematical principles of the airborne induced polarization (IP) method. The possibility of extracting information about the IP properties of rocks from airborne survey data has become a subject of active research recently. We introduce a method for the joint inversion of the airborne EM data into the electrical conductivity and IP parameters based on the generalized effective-medium theory of induced polarization (GEMTIP). We also present the results of the inversion of the airborne EM data collected over the Echum Project Area, in Northwestern Ontario, Canada, into 3D conductivity and chargeability models. Obtaining IP physical property models from an airborne geophysical survey may result in a paradigm change in mineral exploration by pulling more information and value from airborne EM surveys.

Subject. This article discusses the issues of the relevant reflection of intellectual capital, as a relatively new category in the management system of higher education institutions, in the KPI system. Objectives. The article aims to systematize and assess the completeness and relevance of information on intellectual capital in the KPI performance indicator system of the Financial University under the Government of the Russian Federation. Methods. For the study, we used the methods of quantitative and systematic analysis, grouping and generalization of data, a systems approach, the composition of logical relationships, and the formulation of critical comments and conclusions. Results. Based on the analysis of the indicators of the leading Russian university regarding the full disclosure of information about intellectual capital in the published strategic reporting, taking into account foreign experience in the formation of KPI of intellectual capital by European universities and general indicators developed by the international organization World Intellectual Capital Initiative (WICI), the article reveals WICI indicators describing the state of client capital objects that can be adapted to the specifics of scientific and educational activities and included in the KPI of the Financial University. Conclusions. Indicators characterizing the state and development of human and structural capital were found in the reporting of foreign universities. They are not reflected in the Development Programme of the Financial University and are of interest for further improving the system of performance indicators of the University.

Abstract In the Lac de Gras (LDG) kimberlite field, Northwest Territories, Canada, coherent kimberlites (CKs) occur as tabular dykes, pipe-shaped diatremes, and irregular bodies without well-defined geometries. Combining the morphology of CK bodies with the occurrence of fragmented olivine microcrysts allows distinction of four CK types at LDG: (1) dykes with no broken olivine; (2) CK without well-defined but probable sheet geometry and no broken olivine; (3) pipe-filling CK (pfCK) with abundant broken olivine and (4) pfCK with no broken olivine. These features suggest an intrusive origin for type 1 and, probably, type 2 CK; a high-energy extrusive emplacement for CK type 3 and a low-energy intrusive or extrusive emplacement for the CK type 4. Here, we compare petrographic and whole-rock, olivine and spinel compositional data for high-energy extrusive pfCK, low-energy pfCK and intrusive CK units to understand the factors controlling their variable emplacement styles. Extrusive CK contain more abundant groundmass phlogopite and monticellite, lower carbonate/silicate mineral abundance ratios and significantly lower dolomite and pleonaste-spinel abundances compared to intrusive CK. This indicates greater CO2 loss and higher H2O/CO2 in the melt phase for the extrusive CK during emplacement. Lower incompatible element concentrations in the extrusive CKs and different chromite Ti# and olivine rim Mg# indicate derivation from distinct primitive melt compositions. The extrusive CK feature higher ɛNdi and marginally higher ɛHfi compositions than the intrusive CK, pointing to derivation from distinct sources. These findings strongly imply that distinct primary melt compositions were largely responsible for the differences in emplacement styles of CK at LDG. Low-energy pfCKs have similar olivine rim Mg#, chromite Ti# and, hence, primitive melt compositions to the high-energy extrusive CK samples. Their marginally different emplacement styles may depend on local factors, such as changing stress regimes, or slightly different volatile concentrations. Both types of pfCK might reflect the waning stages of volcanic sequences resulting from the eruption of a segregated magma column that started with pipe excavation and the explosive emplacement of gas-rich magma (volcaniclastic kimberlite), followed by the less energetic emplacement of melt-rich magma (pfCK). This hypothesis underscores different primary melt compositions for dyke vs pipe-forming (and filling) kimberlites and hence a fundamental primary melt control on the explosivity of kimberlites.