Opto-Knowledge Systems (United States)

To meet the need for better analysis of ocean methane, we have developed an in-situ gas sensor, that combines a novel laser absorption spectrometer with a membrane-free approach to water sampling. The sensor was designed for real-time measurements of methane concentration and isotope ratio at depths down to 3000 m and is useful for scientific studies as well as energy exploration. We describe the design, development, and utilization of the sensor. Including presenting data from measurements at deep-sea hydrothermal vents on two recent scientific research cruises: July 2022 and March-April 2023.

A compact infrared absorption spectrometer is developed and integrated with a light-duty unmanned aerial vehicle (UAV) to provide high-resolution, real-time spatial mapping of species concentrations in dynamic atmospheric environments. The multi-species optical sensor is contained within a 0.5 ft3 package that is mounted to a custom fabricated quadrotor UAV. The on-board optical diagnostics record CO and CO2 concentrations which are transmitted in real-time at a rate of 1.25 Hz to a remote monitoring station. The sensor results are synchronized with the UAV GPS system to generate time-histories and spatial maps. The aerial spectrometer was deployed in a series of prescribed forest burns at the UC Berkeley Blodgett Forest Research Station, where it successfully captured transient plume behavior and generated three-dimensional spatial profiles on 100 m spatial scales and altitudes up to 100 m. The measurements presented here aim to demonstrate the potential for high-resolution, UAV-borne optical sensors for atmospheric monitoring in harsh, dynamic environments, while serving as a guide for future technological improvements and applications.

A mid-infrared laser absorption sensing method has been developed to quantify gas properties (temperature, pressure, and species density) at MHz measurement rates, with application to annular rotating detonation rocket flows. Bias-tee circuitry is integrated with distributed feedback quantum cascade and interband cascade lasers in the $$4{-}5~\mu \hbox {m}$$ range enabling diplexed radio frequency (RF) wavelength modulation on the order of several MHz while yielding sufficient scan depth to capture multiple rovibrational transitions in the fundamental vibrational bands of $${\text {CO}}$$ and $${\text {CO}}_{2}$$ . Sub-microsecond spectrally-resolved $${\text {CO}}$$ absorption lineshapes provide for inference of temperature and species from a two-line area ratio and pressure from collision line-width. $${\text {CO}}_{2}$$ column density is inferred from peak-to-valley differential absorption at the bandhead near $$4.19~\mu \hbox {m}$$ . A field demonstration on a methane-oxygen rotating detonation rocket engine was performed utilizing an in situ single-ended retro-reflection optical configuration aligned at the exhaust plane. The target gas properties are temporally-resolved at up to 3 MHz across rotating detonations with up to 20 kHz cycle frequency.

Abstract Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition, and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current semantic annotation practices among the COmputational Modeling in BIology NEtwork (COMBINE) community and provide a set of recommendations for building a consensus approach to semantic annotation.

The California energy crisis in 2000-2001 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This paper presents a flexible and integrative method to assess market designs through agent-based modeling. Realistic simulation scenarios are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GENCO) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power.

Time critical search & rescue (s&r) operations often requires the detection of small objects in a vast area. While an airborne search can cover the area, no operational instrumental tools currently exist to actually replace the human operator. By producing the spectral signature of each pixel in a spatial image, multi- and hyper-spectral imaging (HSI) sensors provides a powerful capability for automated detection of subpixel size objects that are otherwise unresolved objects in conventional imagery. This property of HSI naturally lends itself to s&r operations. A lost hiker, skier, life raft adrift in the ocean, downed pilot or small aircraft wreckage targets, can be detected from relatively high altitude based on their unique spectral signatures. Moreover, the spectral information obtained allows the search craft to operate at substantially reduced spatial resolution thereby increasing scene coverage without a significant loss in detection sensitivity. The paper demonstrates the detection of objects as small as 1/10 of an image pixel from a sensor flying at over 6 km altitude. A subpixel object detection algorithm using HSI, based on local image statistics without reliance on spectral libraries is presented. The technique is amenable to fast signal processing and the requisite hardware can be built using inexpensive off the shelf technology. This makes HSI a highly attractive tool for real-time, autonomous instrument-based implementation. It can complement current visual-based s&r operations or emerging synthetic aperture radar sensors that are much more expensive.