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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2005

New high performance algorithmic solution for diagnosis problem

In this paper we address the problem of generating the minimal diagnosis from the conflicts. This problem can be formulated as the well-known Hitting Set Problem. Our approach starts by mapping the Hitting Set problem into the Integer Programming Problem that enables us, for the first time, a priori determination of the lower and upper bounds on the size for the solution. Based on these bounds, we introduce a new concept of solution window for the problem. We also propose a new branch-and-bound technique that not only is faster than the current techniques in terms of number of operations (by exploiting the structure of the problem) but also, using the concept of window, allows a massive reduction (pruning) in the number of branches. Furthermore, as the branch-and-bound proceeds, the solution window is dynamically updated and narrowed to enable further pruning.

diagnosis problems↗
NASA NTRS2007

Assessing MMOD Impacts on Seal Performance

The elastomer seal needed to seal in cabin air when NASA s Crew Exploration Vehicle is docked is exposed to space prior to docking. While open to space, the seal might be hit by orbital debris or meteoroids. The likelihood of damage of this type depends on the size of the particle. Our campaign is designed to find the smallest particle that will cause seal failure resulting in loss of mission. We will then be able to estimate environmental risks to the seal. Preliminary tests indicate seals can withstand a surprising amount of damage and still function. Collaborations with internal and external partners are in place and include seal leak testing, modeling of the space environment using a computer code known as BUMPER, and hypervelocity impact (HVI) studies at Caltech. Preliminary work at White Sands Test Facility showed a 0.5 mm diameter HVI damaged areas about 7 times that diameter, boring deep (5 mm) into elastomer specimens. BUMPER simulations indicate there is a 1 in 1440 chance of getting hit by a particle of diameter 0.08 cm for current Lunar missions; and 0.27 cm for a 10 year ISS LIDS seal area exposure.

deGroh, Henry C., III↗
NASA NTRS2009

Hail Monitor Sensor

An inexpensive and simple hail monitor design has been developed that has a single piezoelectric ceramic disc and uses a metal plate as a sounding board. The structure is durable and able to withstand the launch environment. This design has several advantages over a multi-ceramic sensor, including reduced cost and complexity, increased durability, and improvement in impact response uniformity over the active surface. However, the most important characteristic of this design is the potential to use frequency discrimination between the spectrum created from raindrop impact and a hailstone impact. The sound of hail hitting a metal plate is distinctly different from the sound of rain hitting the same plate. This fortuitous behavior of the pyramid sensor may lead to a signal processing strategy, which is inherently more reliable than one depending on amplitude processing only. The initial concept has been im proved by forming a shallow pyramid structure so that hail is encouraged to bounce away from the sensor so as not to be counted more than once. The sloped surface also discourages water from collecting. Additionally, the final prototype version includes a mounting box for the piezo-ceramic, which is offset from the pyramid apex, thus helping to reduce non-uniform response (see Figure 2). The frequency spectra from a single raindrop impact and a single ice ball impact have been compared. The most notable feature of the frequency resonant peaks is the ratio of the 5.2 kHz to 3.1 kHz components. In the case of a raindrop, this ratio is very small. But in the case of an ice ball, the ratio is roughly one third. This frequency signature of ice balls should provide a robust method for discriminating raindrops from hailstones. Considering that hail size distributions (HSDs) and fall rates are roughly 1 percent that of rainfall, hailstone sizes range from a few tenths of a centimeter to several centimeters. There may be considerable size overlap between large rain and small hail. As hail occurs infrequently at KSC, the ideal HSD measurement sensor needs to have a collection area roughly 100 times greater than a raindrop-size distribution sensor or disdrometer. The sensitivity should be such that it can detect and count very small hail in the midst of intense rainfall consisting of large raindrop sizes. The dynamic range and durability should allow measurement of the largest hail sizes, and the operation and calibration strategy should consider the infrequent occurrence of hail fall over the KSC area.

Younquist, Robert↗
NASA NTRS2001

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

Mengshoel, Ole J.↗
NASA NTRS2005

Biased Randomized Algorithm for Fast Model-Based Diagnosis

A biased randomized algorithm has been developed to enable the rapid computational solution of a propositional- satisfiability (SAT) problem equivalent to a diagnosis problem. The closest competing methods of automated diagnosis are described in the preceding article "Fast Algorithms for Model-Based Diagnosis" and "Two Methods of Efficient Solution of the Hitting-Set Problem" (NPO-30584), which appears elsewhere in this issue. It is necessary to recapitulate some of the information from the cited articles as a prerequisite to a description of the present method. As used here, "diagnosis" signifies, more precisely, a type of model-based diagnosis in which one explores any logical inconsistencies between the observed and expected behaviors of an engineering system. The function of each component and the interconnections among all the components of the engineering system are represented as a logical system. Hence, the expected behavior of the engineering system is represented as a set of logical consequences. Faulty components lead to inconsistency between the observed and expected behaviors of the system, represented by logical inconsistencies. Diagnosis - the task of finding the faulty components - reduces to finding the components, the abnormalities of which could explain all the logical inconsistencies. One seeks a minimal set of faulty components (denoted a minimal diagnosis), because the trivial solution, in which all components are deemed to be faulty, always explains all inconsistencies. In the methods of the cited articles, the minimal-diagnosis problem is treated as equivalent to a minimal-hitting-set problem, which is translated from a combinatorial to a computational problem by mapping it onto the Boolean-satisfiability and integer-programming problems. The integer-programming approach taken in one of the prior methods is complete (in the sense that it is guaranteed to find a solution if one exists) and slow and yields a lower bound on the size of the minimal diagnosis. In contrast, the present approach is incomplete and fast and yields an upper bound on the size of the minimal diagnosis.

Williams, Colin↗
NASA NTRS2011

Binomial Test Method for Determining Probability of Detection Capability for Fracture Critical Applications

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.

Generazio, Edward R.↗
NASA NTRS2013

A Signal Detection Theory Approach to Evaluating Oculometer Data Quality

Currently, data quality is described in terms of spatial and temporal accuracy and precision [Holmqvist et al. in press]. While this approach provides precise errors in pixels, or visual angle, often experiments are more concerned with whether subjects'points of gaze can be said to be reliable with respect to experimentally-relevant areas of interest. This paper proposes a method to characterize oculometer data quality using Signal Detection Theory (SDT) [Marcum 1947]. SDT classification results in four cases: Hit (correct report of a signal), Miss (failure to report a ), False Alarm (a signal falsely reported), Correct Reject (absence of a signal correctly reported). A technique is proposed where subjects' are directed to look at points in and outside of an AOI, and the resulting Points of Gaze (POG) are classified as Hits (points known to be internal to an AOI are classified as such), Misses (AOI points are not indicated as such), False Alarms (points external to AOIs are indicated as in the AOI), or Correct Rejects (points external to the AOI are indicated as such). SDT metrics describe performance in terms of discriminability, sensitivity, and specificity. This paper presentation will provide the procedure for conducting this assessment and an example of data collected for AOIs in a simulated flightdeck environment.

Latorella, Kara↗
NASA NTRSDate not supplied

Assessing the Viability of Using GEOS-Forecast Product for Landslides Forecasting: A Step Toward Early Warning System

Landslides across the globe are mostly triggered by extreme rainfall events affecting infrastructure, transportation and livelihoods. The risks are rarely quantified due to lack of data, analytical skills and limited modeling techniques. Knowledge of local to global scale landslide risks provides communities and national agencies the ability to adapt disaster management practices to mitigate and recover from these hazards. In order to minimize the risks and improve characterization of community resilience to landslides, it is vital to have reliable information about the factors triggering landslides such as rainfall, well ahead in time. Forecasting potential landslide activity and impacts can be achieved through reliable precipitation forecast models. However, it is challenging because of the temporal and spatial variability of precipitation, an important factor in triggering landslides. Evaluation of the precipitation field, associated errors, and sampling uncertainties is integral for development of efficient and reliable landslide forecasting and early warning system. This study develops a methodology to assess the viability of using a precipitation field provided by a global model and its potential integration in the landslide forecasting system. The study focuses on the comparison between the IMERG (Integrated Multi-satellitE Retrievals for Global Precipitation Mission) and GEOS (NASA Goddard Earth Observing System)-Forecast product over contiguous United States (CONUS). GEOS model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The framework is tested on the GEOS-Forecast Model initialized at 00 UTC using daily IMERG early product as reference using both categorical and continuous statistics. The categorical statistics includes the probability of detection (POD), success ratio (SR), critical success index (CSI), and the hit bias. Continuous statistics such as correlation, normalized standard deviation, and root-mean-square error are also evaluated. Overall, GEOS-Forecast precipitation field over the analysis period (~1 year) show underestimation with respect to IMERG early for the daily accumulated rainfall. However, the probability distribution function and cumulative distribution function of both show similar patterns. In terms of correlations, POD, SR, CSI, hit bias, the performance varies with respect to the rainfall threshold used.

Sana Khan↗
NASA NTRS2021

Validation of Satellite-Based Precipitation Products from TRMM to GPM

The global precipitation measurement mission (GPM) has been in operation for seven years and continues to provide a vast quantity of global precipitation data at finer temporospatial resolutions with improved accuracy and coverage. GPM’s signature algorithm, the integrated multisatellite retrievals for GPM (IMERG) is a next-generation of precipitation product expected for wide variety of research and operational applications. This study evaluates the latest version (V06B) of IMERG and its predecessor, the tropical rainfall measuring mission (TRMM) multisatellite precipitation (TMPA) 3B42 (V7) using ground-based and gauge-corrected multiradar multisensor system (MRMS) precipitation products over the conterminous United States (CONUS). The spatial distributions of all products are analyzed. The error characteristics are further examined for 3B42 and IMERG in winter and summer by an error decomposition approach, which partitions total bias into hit bias, biases due to missed precipitation and false precipitation. The volumetric and categorical statistical metrics are used to quantitatively evaluate the performance of the two satellite-based products. All products show a similar precipitation climatology with some regional differences. The two satellite-based products perform better in the eastern CONUS than in the mountainous Western CONUS. The evaluation demonstrates the clear improvement in IMERG precipitation product in comparison with its predecessor 3B42, especially in reducing missed precipitation in winter and summer, and hit bias in winter, resulting in better performance in capturing lighter and heavier precipitation.

MRMS↗
NASA NTRSDate not supplied

Comparison of Active and Passive Head Impulse Testing of the Horizontal Vestibulo-Ocular Reflex: Exploring the Feasibility of Different Approaches for Spaceflight

INTRODUCTION: Astronauts experience a wide variety of sensorimotor disturbances primarily due to microgravity-induced vestibular adaptations during spaceflight. Head Impulse Testing (HIT) will be conducted during the Complement of Integrated Protocols for Human Exploration Research program(CIPHER) Vestibular Health study to examine changes in the horizontal vestibulo-ocular reflex in response to high-velocity head movements to detect changes in peripheral vestibular function [1,2]. However, correct interpretation will require consideration of potential artifacts and the constraints of conducting this test across different phases of the mission. Therefore, the aims of our study were to (1) examine reliability across different test operators, and (2) compare results of active (aHIT) versus passive (pHIT) approaches to evaluate the feasibility of self-administered versus operator-assisted approaches. A comparison of responses with visual viewing of a wall target (default condition) versus vision occluded evaluated the influence of other oculomotor control influence across conditions, and comparison with computer-generated rotator head impulse tests (rHIT) examined the variability associated with the ocular responses independent of the variability in executing the head movements themselves. METHODS: Seventeen non-astronaut volunteers (male n=12, age=22.9 ± 3.0; female n=5, age=27.0 ± 6.0, mean ± std) completed HIT testing using video-oculography (VOG) goggles and a high-torque rotator system. The test order was counterbalanced across conditions: (1) passive head-on-torso (pHIT, default condition for flight study) using two operators (Op1 and Op2), (2) active head-on-torso (aHIT, subject initiated), and (3) passive head and torso using rotary chair (rHIT). Eye and head movement data were processed to obtain gain in each direction. The main outcome measures were average gain and asymmetry [1], as well as the percentage of acceptable trials not excluded due to insufficient head amplitude or recording artifacts. RESULTS: While the pHIT gains were similar with vision (1.032 ± 0.043) and vision occluded (1.029 ± 0.038) conditions, the percentage of acceptable trials was greater with vision (Op1 = 93.0%, Op2 = 93.2%) versus occluded (Op1 = 70.7%, Op2 = 67.6%). The reliability between operators was greater for pHIT gain (Intraclass Correlation, ICC = 0.66, p = 0.001) than for pHIT asymmetry (ICC = 0.57, p = 0.01). The percentage of acceptable trials reduced by ~20% during the self-administered aHITs for both visual conditions and tended to be lower than computer-generated rHITs (76% versus 83%). While the aHIT gains were not significantly different than pHIT gains for vision or vision occluded conditions, these measures were poorly correlated. Both aHIT and pHIT gains were significantly greater than the rHIT gains, presumably due to the reduced velocities from the rotator. The asymmetry measures were poorly correlated across pHIT, aHIT, and rHIT conditions, although none of the subjects had asymmetries greater than 16%. DISCUSSION: Our findings support the feasibility of using the standard pHIT methodology for spaceflight. Similarities between visual conditions reflect that these responses are mediated by the peripheral lateral canals rather than other oculomotor mechanisms. The inter-tester reliability was acceptable despite differences in the tester training. In addition to concerns of non-vestibular mechanisms introduced during self-administered aHITs [2], operator-assisted pHITs resulted in higher percentage of acceptable trials and should result in more efficient and reliable measures during spaceflight.

M R Ehrenburg↗
NASA NTRS2024

Multi-Agency Ensemble Forecast of Wildfire Air Quality in the United States: Toward Community Consensus of Early Warning

Wildfires pose increasing risks to human health and properties in North America. Due to large uncertainties in fire emission, transport, and chemical transformation, it remains challenging to accurately predict air quality during wildfire events, hindering our collective capability to issue effective early warnings to protect public health and welfare. Here we present a new real-time Hazardous Air Quality Ensemble System (HAQES) by leveraging various wildfire smoke forecasts from three U.S. federal agencies (NOAA, NASA, and Navy). Compared to individual models, the HAQES ensemble forecast significantly enhances forecast accuracy. To further enhance forecasting performance, a weighted ensemble forecast approach was introduced and tested. Compared to the unweighted ensemble mean, the multilinear regression weighted ensemble reduced fractional bias by 34% in the major fire regions, false alarm rate by 72%, and increased hit rate by 17%. Finally, we improved the weighted ensemble using quantile regression and weighted regression methods to enhance the forecast of extreme air quality events. The advanced weighted ensemble increased the PM2.5 exceedance hit rate by 55% compared to the ensemble mean. Our findings provide insights into the development of advanced ensemble forecast methods for wildfire air quality, offering a practical way to enhance decision-making support to protect public health.

Yunyao Li↗
DOE OSTI2020

A pixel detector ROIC with a 3-bit, 40 Msps synchronous ADC per pixel for HL LHC

The prototype Fermi Compact Muon Solenoid (CMS) Pixel (FCP130), manufactured in a 130 nm process, is a readout integrated circuit (ROIC) designed for the High Luminosity upgrade of the Large Hadron Collider. It employs a synchronous analog to digital converter (ADC) for the front-end design, with signal processing and data conversion within a single bunch crossing of 25 ns. It is therefore capable of accurately detecting hits occurring in consecutive bunch crossings, without off-time registration of events, making it particularly suitable for the inner most layers of the vertex detector. The ROIC consists of a matrix of 48 × 160 pixels, each 100 × 30 μm2 in size. Each pixel contains a charge sensitive preamplifier with self-biasing leakage current compensation, eight auto-zero comparators and a Gray code encoder for a 3-bit flash-type ADC. The total power consumption is approximately 24 μW per pixel. The measured noise at the output of all the hit comparators across the ROIC is < 80 e- with threshold dispersion < 110 e-RMS, which allows an in-time threshold setting of ~ 1000 e-.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Track Seeding and Labelling with Embedded-space Graph Neural Networks

To address the unprecedented scale of HL-LHC data, the Exa.TrkX project is investigating a variety of machine learning approaches to particle track reconstruction. The most promising of these solutions, graph neural networks (GNN), process the event as a graph that connects track measurements (detector hits corresponding to nodes) with candidate line segments between the hits (corresponding to edges). Detector information can be associated with nodes and edges, enabling a GNN to propagate the embedded parameters around the graph and predict node-, edge- and graph-level observables. Previously, message-passing GNNs have shown success in predicting doublet likelihood, and we here report updates on the state-of-the-art architectures for this task. In addition, the Exa.TrkX project has investigated innovations in both graph construction, and embedded representations, in an effort to achieve fully learned end-to-end track finding. Hence, we present a suite of extensions to the original model, with encouraging results for hitgraph classification. In addition, we explore increased performance by constructing graphs from learned representations which contain non-linear metric structure, allowing for efficient clustering and neighborhood queries of data points. We demonstrate how this framework fits in with both traditional clustering pipelines, and GNN approaches. The embedded graphs feed into high-accuracy doublet and triplet classifiers, or can be used as an end-to-end track classifier by clustering in an embedded space. A set of post-processing methods improve performance with knowledge of the detector physics. Finally, we present numerical results on the TrackML particle tracking challenge dataset, where our framework shows favorable results in both seeding and track finding.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A Low-Power Time-to-Digital Converter for the CMS Endcap Timing Layer (ETL) Upgrade

We present the design and test results of a Time-to-Digital-Converter (TDC). The TDC will be a part of the readout ASIC, called ETROC, to read out Low-Gain Avalanche Detectors (LGADs) for the CMS Endcap Timing Layer (ETL) of High-Luminosity LHC upgrade. One of the challenges of the ETROC design is that the TDC is required to consume less than 200 W for each pixel at the nominal hit occupancy of 1%. To meet the low-power requirement, we use a single delay line for both the Time of Arrival (TOA) and the Time over Threshold (TOT) measurements without delay control. A double-strobe self-calibration scheme is used to compensate for process variation, temperature, and power supply voltage. The TDC is fabricated in a 65 nm CMOS technology. The overall performances of the TDC have been evaluated. The TOA has a bin size of 17.8 ps within its effective dynamic range of 11.6 ns. The effective measurement precision of the TOA is 5.6 ps and 9.9 ps with and without the nonlinearity correction, respectively. The TDC block consumes 97 W at the hit occupancy of 1%. Over a temperature range from 23 C to 78 C and a power supply voltage range from 1.05 V to 1.35 V (the nominal value of 1.20 V), the self-calibrated bin size of the TOA varies within 0.4%. The measured TDC performances meet the requirements except that more tests will be performed in the future to verify that the TDC complies with the radiation-tolerance specifications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Method and apparatus for mitigating row hammer attacks

An integrated circuit includes an aggressor wordline cache and logic that determines a candidate upper adjacent address and a candidate lower adjacent address of a target memory row corresponding to a read request to memory. When at least one of the candidate upper adjacent address or the candidate lower adjacent address are determined to be a victim row, the logic checks the aggressor wordline cache for a cache hit for the target memory row. When there is a cache hit in the aggressor wordline cache, the logic sends a corresponding cache line as a response to the read request, otherwise the logic causes a read of content from the memory. In certain examples, the logic includes a stored bit array and a hash function-based filter, which determines whether any of the candidate upper adjacent address and the candidate lower adjacent address are victim rows represented in the stored bit array.

SeyedzadehDelcheh, SeyedMohammad↗
DOE OSTI2021

A 3D FPGA Track Segment Seeding Engine Based on the Tiny Triplet Finder

A 3D track segment seeding engine core based on the Tiny Triplet Finder has been implemented and tested in a low-cost FPGA device. The seeding engine is designed to preselect and group hits (stubs) from cylindrical detector layers to feed subsequent track fitting stage. The seeding engine consists of a Hough transform space for r-z view and a Tiny Triplet Finder for r-phi view to implement 3D constraints. The seeding engine is organized as a pipeline so that each hit is processed in a single clock cycle. Test results show that the seeding engine operates as expected.

Wu, Jinyuan↗
DOE OSTI2020

The Analog Front-end for the LGAD Based Precision Timing Application in CMS ETL

The analog front-end for the Low Gain Avalanche Detector (LGAD) based precision timing application in the CMS Endcap Timing Layer (ETL) has been prototyped in a 65 nm CMOS mini-ASIC named ETROC0. Serving as the very first prototype of ETL readout chip (ETROC), ETROC0 aims to study and demonstrate the performance of the analog frontend, with the goal to achieve 40 to 50 ps time resolution per hit with LGAD (therefore reach about 30ps per track with two detector-layer hits per track). ETROC0 consists of preamplifier and discriminator stages, which amplifies the LGAD signal and generates digital pulses containing time of arrival and time over threshold information. This paper will focus on the design considerations that lead to the ETROC front-end architecture choice, the key design features of the building blocks, the methodology of using the LGAD simulation data to evaluate and optimize the front-end design. The ETROC0 prototype chips have been extensively tested using charge injection and the measured performance agrees well with simulation. The initial beam test results are also presented, with time resolution of around 33 ps observed from the preamplifier waveform analysis and around 41 ps from the discriminator pulses analysis. A subset of ETROC0 chips have also been tested to a total ionizing dose of 100 MRad with X-ray and no performance degradation been observed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

In-Pixel Readout IC with compact in-pixel ADC for Pixel detectors at HL LHC

The prototype Smart Pixel concept test chip (SP28), designed in a CMOS 28 nm bulk process, is a proof of concept readout integrated circuit (ROIC) designed for a future Phase III High Luminosity upgrade of the Large Hadron Collider. It employs a synchronous analog to digital converter (ADC) for the front-end design, with signal processing and data conversion within a single bunch crossing of 25 ns. It is therefore capable of accurately detecting hits occurring in consecutive bunch crossings, without off-time registration of events and pileup insensitivity, making it particularly suitable for the inner most layers of the vertex detector. The ROIC consists of a matrix of 32 × 16 pixels, each 25 × 25 µm 2 in size. Each pixel contains a charge sensitive preamplifer with leakage current compensation, three auto-zero comparators for a 2-bit fash-type ADC. The total power consumption is approximately 5 µW per pixel. The measured noise at the output of all the hit comparators across the ROIC is < 90 e- with threshold dispersion < 45 e-RMS, which allows an in-time threshold setting of ≈ 475 e-.

Parpillon, Benjamin↗