Geothermal power plants are excellent resources for providing low carbon electricity generation with high reliability. However, many geothermal power plants could realize significant improvements in ...operational efficiency from the application of improved modeling software. Increased integration of digital twins into geothermal operations will not only enable engineers to better understand the complex interplay of components in larger systems but will also enable enhanced exploration of the operational space with the recent advances in artificial intelligence (AI) and machine learning (ML) tools. Such innovations in geothermal operational analysis have been deterred by several challenges, most notably, the challenge in applying idealized thermodynamic models to imperfect as-built systems with constant degradation of nominal performance. This paper presents GOOML: a new framework for Geothermal Operational Optimization with Machine Learning. By taking a hybrid data-driven thermodynamics approach, GOOML is able to accurately model the real-world performance characteristics of as-built geothermal systems. Further, GOOML can be readily integrated into the larger AI and ML ecosystem for true state-of-the-art optimization. This modeling framework has already been applied to several geothermal power plants and has provided reasonably accurate results in all cases. Therefore, we expect that the GOOML framework can be applied to any geothermal power plant around the world.
Fiber-optic cables can provide a wealth of detailed data on subsurface vibrations from a wide range of sources. Machine learning offers a means to make sense of it all.
•We successfully modified the PFA methodology to identify favorable areas for superhot EGS at Newberry Volcano in 3D.•Key components of superhot EGS plays were developed, including heat source, ...thermal insulation, and producibility.•Uncertainty was also quantified in 3D for datasets which provided enough information to do so.•Two different methods were used to weight exploration datasets, and the resulting favorability models compared.
The DErisking Exploration for multiple geothermal Plays in magmatic ENvironments (DEEPEN) project aims to de-risk exploration of geothermal plays in magmatic systems, with a focus on superhot and supercritical geothermal systems. This article presents advancements in geoscientific assessment of superhot enhanced geothermal system (EGS) resources as part of the DEEPEN project, particularly in exploration and identification of these systems. While there exists a general consensus on key components of conventional hydrothermal systems, there has not been a prior consensus on such components for EGS, let alone superhot EGS. The DEEPEN project identified these key components for superhot EGS plays, and used them to modify the traditional geothermal play fairway analysis (PFA) approach to identify favorable areas in superhot EGS plays in 3D. This was done through modeling both favorability and uncertainty separately for each key component of a superhot EGS play, incorporating diverse 3D geoscientific datasets, including geologic features, models produced from direct observations, single inversions, and joint inversions. The PFA is applied to Newberry Volcano as a form of validation. The results appear to validate the methodology, aligning with expectations derived from conceptual modeling, and highlighting the area targeted for EGS stimulation well NWG 55-29 as favorable, and suggesting potential additional areas worthy of exploration at Newberry.
The DErisking Exploration for multiple geothermal Plays in magmatic ENvironments (DEEPEN) project aims to de-risk exploration of geothermal plays in magmatic systems, with a focus on superhot and ...supercritical geothermal systems. This article presents advancements in geoscientific assessment of superhot enhanced geothermal system (EGS) resources as part of the DEEPEN project, particularly in exploration and identification of these systems. While there exists a general consensus on key components of conventional hydrothermal systems, there has not been a prior consensus on such components for EGS, let alone superhot EGS. The DEEPEN project identified these key components for superhot EGS plays, and used them to modify the traditional geothermal play fairway analysis (PFA) approach to identify favorable areas in superhot EGS plays in 3D. This was done through modeling both favorability and uncertainty separately for each key component of a superhot EGS play, incorporating diverse 3D geoscientific datasets, including geologic features, models produced from direct observations, single inversions, and joint inversions. The PFA is applied to Newberry Volcano as a form of validation. Finally, the results appear to validate the methodology, aligning with expectations derived from conceptual modeling, and highlighting the area targeted for EGS stimulation well NWG 55-29 as favorable, and suggesting potential additional areas worthy of exploration at Newberry.
Attenuated Listeria monocytogenes (Lm
-LLO) represents a valuable anticancer vaccine and drug delivery platform. Here we show that in vitro Lm
-LLO causes ROS production and, in turn, apoptotic ...killing of a wide variety of melanoma cells, irrespectively of their stage, mutational status, sensitivity to BRAF inhibitors or degree of stemness. We also show that, when administered in the therapeutic setting to Braf/Pten genetically engineered mice, Lm
-LLO causes a strong decrease in the size and volume of primary melanoma tumors, as well as a reduction of the metastatic burden. At the molecular level, we confirm that the anti-melanoma activity exerted in vivo by Lm
-LLO depends also on its ability to potentiate the immune response of the organism against the infected tumor. Our data pave the way to the preclinical testing of listeria-based immunotherapeutic strategies against metastatic melanoma, using a genetically engineered mouse rather than xenograft models.
Abstract Black hole X-ray binaries exhibit different spectral and timing properties in different accretion states. The X-ray outburst of a recently discovered and extraordinarily bright source, Swift ...J1727.8–1613, has enabled the first investigation of how the X-ray polarization properties of a source evolve with spectral state. The 2–8 keV polarization degree was previously measured by the Imaging X-ray Polarimetry Explorer (IXPE) to be ≈4% in the hard and hard intermediate states. Here we present new IXPE results taken in the soft state, with the X-ray flux dominated by the thermal accretion disk emission. We find that the polarization degree has dropped dramatically to ≲1%. This result indicates that the measured X-ray polarization is largely sensitive to the accretion state and the polarization fraction is significantly higher in the hard state when the X-ray emission is dominated by upscattered radiation in the X-ray corona. The combined polarization measurements in the soft and hard states disfavor a very high or low inclination of the system.
Black-hole X-ray binaries exhibit different spectral and timing properties in different accretion states. The X-ray outburst of a recently discovered and extraordinarily bright source, ...Swift\(~\)J1727.8\(-\)1613, has enabled the first investigation of how the X-ray polarization properties of a source evolve with spectral state. The 2\(-\)8 keV polarization degree was previously measured by the Imaging X-ray Polarimetry Explorer (IXPE) to be \(\approx\) 4% in the hard and hard intermediate states. Here we present new IXPE results taken in the soft state, with the X-ray flux dominated by the thermal accretion-disk emission. We find that the polarization degree has dropped dramatically to \(\lesssim\) 1%. This result indicates that the measured X-ray polarization is largely sensitive to the accretion state and the polarization fraction is significantly higher in the hard state when the X-ray emission is dominated by up-scattered radiation in the X-ray corona. The combined polarization measurements in the soft and hard states disfavor a very high or low inclination of the system.
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