266 research outputs found
The ARIEL Instrument Control Unit design for the M4 Mission Selection Review of the ESA's Cosmic Vision Program
The Atmospheric Remote-sensing Infrared Exoplanet Large-survey mission
(ARIEL) is one of the three present candidates for the ESA M4 (the fourth
medium mission) launch opportunity. The proposed Payload will perform a large
unbiased spectroscopic survey from space concerning the nature of exoplanets
atmospheres and their interiors to determine the key factors affecting the
formation and evolution of planetary systems. ARIEL will observe a large number
(>500) of warm and hot transiting gas giants, Neptunes and super-Earths around
a wide range of host star types, targeting planets hotter than 600 K to take
advantage of their well-mixed atmospheres. It will exploit primary and
secondary transits spectroscopy in the 1.2-8 um spectral range and broad-band
photometry in the optical and Near IR (NIR). The main instrument of the ARIEL
Payload is the IR Spectrometer (AIRS) providing low-resolution spectroscopy in
two IR channels: Channel 0 (CH0) for the 1.95-3.90 um band and Channel 1 (CH1)
for the 3.90-7.80 um range. It is located at the intermediate focal plane of
the telescope and common optical system and it hosts two IR sensors and two
cold front-end electronics (CFEE) for detectors readout, a well defined process
calibrated for the selected target brightness and driven by the Payload's
Instrument Control Unit (ICU).Comment: Experimental Astronomy, Special Issue on ARIEL, (2017
Design for testability in hardware-software systems
Clearly, in today's complex systems, hardware and software approaches to DFT must work together to achieve a successful overall solution. The authors investigate existing and new concepts that may lead to a single design for test strategy in the futur
Product assurance technology for custom LSI/VLSI electronics
The technology for obtaining custom integrated circuits from CMOS-bulk silicon foundries using a universal set of layout rules is presented. The technical efforts were guided by the requirement to develop a 3 micron CMOS test chip for the Combined Release and Radiation Effects Satellite (CRRES). This chip contains both analog and digital circuits. The development employed all the elements required to obtain custom circuits from silicon foundries, including circuit design, foundry interfacing, circuit test, and circuit qualification
The STAR MAPS-based PiXeL detector
The PiXeL detector (PXL) for the Heavy Flavor Tracker (HFT) of the STAR
experiment at RHIC is the first application of the state-of-the-art thin
Monolithic Active Pixel Sensors (MAPS) technology in a collider environment.
Custom built pixel sensors, their readout electronics and the detector
mechanical structure are described in detail. Selected detector design aspects
and production steps are presented. The detector operations during the three
years of data taking (2014-2016) and the overall performance exceeding the
design specifications are discussed in the conclusive sections of this paper
Lunar Surface Systems Supportability Technology Development Roadmap
The Lunar Surface Systems Supportability Technology Development Roadmap is a guide for developing the technologies needed to enable the supportable, sustainable, and affordable exploration of the Moon and other destinations beyond Earth. Supportability is defined in terms of space maintenance, repair, and related logistics. This report considers the supportability lessons learned from NASA and the Department of Defense. Lunar Outpost supportability needs are summarized, and a supportability technology strategy is established to make the transition from high logistics dependence to logistics independence. This strategy will enable flight crews to act effectively to respond to problems and exploit opportunities in an environment of extreme resource scarcity and isolation. The supportability roadmap defines the general technology selection criteria. Technologies are organized into three categories: diagnostics, test, and verification; maintenance and repair; and scavenge and recycle. Furthermore, "embedded technologies" and "process technologies" are used to designate distinct technology types with different development cycles. The roadmap examines the current technology readiness level and lays out a four-phase incremental development schedule with selection decision gates. The supportability technology roadmap is intended to develop technologies with the widest possible capability and utility while minimizing the impact on crew time and training and remaining within the time and cost constraints of the program
AI/ML Algorithms and Applications in VLSI Design and Technology
An evident challenge ahead for the integrated circuit (IC) industry in the
nanometer regime is the investigation and development of methods that can
reduce the design complexity ensuing from growing process variations and
curtail the turnaround time of chip manufacturing. Conventional methodologies
employed for such tasks are largely manual; thus, time-consuming and
resource-intensive. In contrast, the unique learning strategies of artificial
intelligence (AI) provide numerous exciting automated approaches for handling
complex and data-intensive tasks in very-large-scale integration (VLSI) design
and testing. Employing AI and machine learning (ML) algorithms in VLSI design
and manufacturing reduces the time and effort for understanding and processing
the data within and across different abstraction levels via automated learning
algorithms. It, in turn, improves the IC yield and reduces the manufacturing
turnaround time. This paper thoroughly reviews the AI/ML automated approaches
introduced in the past towards VLSI design and manufacturing. Moreover, we
discuss the scope of AI/ML applications in the future at various abstraction
levels to revolutionize the field of VLSI design, aiming for high-speed, highly
intelligent, and efficient implementations
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