CAN UNCLASSIFIED

Defence Research and Development Canada External Literature (P) DRDC-RDDC-2017-P092 November 2017

CAN UNCLASSIFIED

Standoff High Energy Laser Induced Oxidation Spectroscopy (HELIOS) J.-F. Daigle D. Pudo F. Théberge Publisher: American Institute of Physics Journal of Applied Physics Issue: 122, 173102 (2017) Pagination info: 173102-1–173102-5 Date of Publication from Ext Publisher: November, 2017

CAN UNCLASSIFIED

© Her Majesty the Queen in Right of Canada (Department of National Defence), 2017 © Sa Majesté la Reine en droit du Canada (Ministère de la Défense nationale), 2017

CAN UNCLASSIFIED

IMPORTANT INFORMATIVE STATEMENTS

The information contained herein is proprietary to Her Majesty and is provided to the recipient on the understanding that it will be used for information and evaluation purposes only. Any commercial use including use for manufacture is prohibited.

Disclaimer: This document is not published by the Editorial Office of Defence Research and Development Canada, an agency of the Department of National Defence of Canada, but is to be catalogued in the Canadian Defence Information System (CANDIS), the national repository for Defence S&T documents. Her Majesty the Queen in Right of Canada (Department of National Defence) makes no representations or warranties, expressed or implied, of any kind whatsoever, and assumes no liability for the accuracy, reliability, completeness, currency or usefulness of any information, product, process or material included in this document. Nothing in this document should be interpreted as an endorsement for the specific use of any tool, technique or process examined in it. Any reliance on, or use of, any information, product, process or material included in this document is at the sole risk of the person so using it or relying on it. Canada does not assume any liability in respect of any damages or losses arising out of or in connection with the use of, or reliance on, any information, product, process or material included in this document.

This document was reviewed for Controlled Goods by Defence Research and Development Canada (DRDC) using the Schedule to the Defence Production Act.

Standoff high energy laser induced oxidation spectroscopy (HELIOS)J.-F. Daigle, D. Pudo, and F. Théberge

Citation: Journal of Applied Physics 122, 173102 (2017);View online: https://doi.org/10.1063/1.4999918View Table of Contents: http://aip.scitation.org/toc/jap/122/17Published by the American Institute of Physics

Standoff high energy laser induced oxidation spectroscopy (HELIOS)

J.-F. Daigle,a) D. Pudo, and F. Th�ebergeDefence Research and Development Canada-Valcartier research centre, Qu�ebec G3J 1X5, Canada

(Received 11 August 2017; accepted 16 October 2017; published online 1 November 2017)

High Energy Lasers (HELs) used for defense applications require operational distances ranging

from few hundred meters to several kilometers. As the distance increases, the incident beam

properties and, consequently, the anticipated effect delivered to the sample become less predictable.

Therefore, the direct observation of the event induced by the laser can become an asset. In this

paper, we propose a novel spectroscopic method that analyses in real time the spectral components

present in the flames produced during the interaction of a HEL with a metallic piece at a long

distance. This method was used on aluminum and carbon steel samples placed 200m away from the

laser system. It was discovered that the aluminum and iron oxides created as a by-product of the

HEL reaction with the samples emitted clear fingerprint signatures that could be detected remotely

using a spectroscopic receiver placed beside the HEL beam director. The real-time assessment of

the laser-induced effect can be achieved by monitoring the temporal evolution of the oxide signa-

tures, hence providing information to the operator about the reaction and the nature of the sample

illuminated. https://doi.org/10.1063/1.4999918

I. INTRODUCTION

Lasers have been used for decades to treat metallic sam-

ples for different purposes such as surface cleaning,1,2 dril-

ling,3 welding,4,5 coating deposition, marking, and cutting.6

This technology has grown sufficiently mature, to the point

where it is already implemented in many industrial sectors

such as car production and ship manufacturing. Their rapid

proliferation and increased reliability triggered the interest of

the defense and security community who could use kilowatt-

class High Energy Lasers7 (HELs) for a variety of applica-

tions,8 one of which being to drill holes through metallic

objects from a standoff location.

Real-time monitoring tools have been developed in the

past few years,9–12 mostly for cutting and welding purposes,

to observe the laser exposed zones and determine whether the

treatment is a success or a failure. As a result, metallic plates

which were not adequately treated could be rejected and the

laser machine could be readjusted for later processing. These

monitoring systems ensure consistency of the treated metallic

plates, resulting in a laser processing tool whose productivity

and reliability have been improved. Methods that involved

real-time correction of the systems were also developed using

closed-loop adaptive techniques. Nevertheless, these methods

were developed solely for industrial applications where the

laser head is positioned at a close (few millimeters to a meter)

distance from the sample in an enclosed environment and

where the profile of the laser spot is both stable and known.

The need for different real-time monitoring methodolo-

gies of the effects of a HEL beam becomes paramount when

the process is done over long ranges in an uncontrolled envi-

ronment. Atmospheric conditions such as turbulence,13 aero-

sols,14 and thermal blooming15 severely distort the shape of

the laser spot on the sample and as such can affect the

performance of the HEL system in achieving its dedicated

task. Whether it is to conclude that the laser can/cannot be

operated effectively in the given conditions or used in a

closed-loop adaptive compensation system, a tool providing

real-time information on the laser-sample interaction could be

of significant interest. Additionally, a monitoring tool could

also be useful to identify the composition or the nature of an

unknown sample illuminated by a HEL beam. Based on the

information gathered, the operator could then determine

whether the interrogated object is of interest or not.

Spectroscopic methods16,17 involving lasers have been

developed for the remote detection and identification of

unknown samples. A popular method is certainly laser-induced

breakdown spectroscopy (LIBS)18 where a laser beam is

focused onto the interrogated object at intensities neighboring

or above GW/cm2 levels. At this point, laser radiation is suffi-

ciently intense to detach bonded electrons from their parent

molecules or atoms leaving behind a plasma comprising

mostly excited atoms and ions which emit fingerprint radiation

when deexcited towards lower energy levels. LIBS has been

used as a monitoring tool for short distance industrial continu-

ous wave (CW) HEL processes.19 However, for standoff oper-

ation, the high laser intensities required for LIBS techniques

impose the use of high peak power unachievable with CW

HELs.20,21

Even though achieving intensity levels sufficiently high

to execute standoff LIBS is impractical with kW-class

CW HELs over long engagement ranges, the interaction of

loosely focused HEL beams with solid objects may result in

intense emission of light from the material plumes ejected

from the sample with a characteristic spectral composition.

In fact, Fig. 1 presents color-calibrated pictures of the inter-

action of a HEL beam focused onto (a) 6061-T6 aluminum

and (b) AISI 1020 carbon steel plates with an intensity of

approximately 7.5 kW/cm2. Both images exhibit a bright

white spot at the laser location surrounded by a colored halo.

While the images are saturated in the vicinity of the laser

a)Author to whom correspondence should be addressed: jean-francois.daigle@

drdc-rddc.gc.ca

0021-8979/2017/122(17)/173102/5/$30.00 122, 173102-1

JOURNAL OF APPLIED PHYSICS 122, 173102 (2017)

spot, the colored halos observed are not artefacts from the

partly overwhelmed sensor.

When a HEL beam is incident onto a target, the energy

absorbed heats up the material and elevates its temperature.

Certain hot objects, in particular metals, tend to oxidize very

rapidly when immersed in an oxygen-filled environment such

as the atmosphere. Being a highly exothermic process, oxida-

tion produces a significant amount of heat that can be absorbed

by the sample to further elevate its temperature, thus accelerat-

ing the oxidation process.

Interestingly, the bright blue color observed in Fig. 1(a)

is dominantly attributed to excited aluminum oxides (AlO),

while the orange glare in Fig. 1(b) originates from the well-

known iron oxide (FeO) orange system. These oxides were

not present in the material before the interaction and have

been produced under the heating action of the HEL source. It

has been demonstrated that the presence of these oxide emis-

sions is a good indicator, and the laser is sufficiently intense

to drill into the sample as opposed to only heating it.22 Similar

signatures have been observed in flame emission spectroscopy

where metallic vapors were burnt and observed using spectro-

scopic instruments.23

In this paper, we propose to use a spectrometer to collect

and analyse the spectral signatures produced by the excited

oxides from a standoff location. The spectroscopic method

named HEL-Induced Oxidation Spectroscopy (HELIOS) has

been tested on aluminum and carbon steel plates using a

commercial all-fiber HEL system capable of 10 kW power

positioned 200m away from the samples. Intense metallic

oxide fingerprint signatures have been observed, thus allow-

ing for the identification of the samples and remote monitor-

ing of the laser interaction event.

II. EXPERIMENTAL METHODS AND RESULTS

Figure 2 presents a schematic of the experimental setup

used for these tests. A commercial fiber-based laser beam

was focused onto a metallic sample placed 200m away using

a refractive beam expander (BEX). The samples consisted of

3.18-mm thick 6061-T6 aluminum and AISI 1020 carbon

steel square plates. The laser power was set to 6 kW, and the

beam was focused on the samples to a peak intensity neigh-

boring 7.5 kW/cm2. However, the effective intensity incident

on the sample was significantly lower as the HEL platform is

not perfectly stabilized against vibrations which lead to

beam motion down the 200m range. Taking the effective

illuminated area into account, the effective peak intensity

was closer to 3 kW/cm2.

A 10-cm diameter Cassegrainian reflective receiver, posi-

tioned besides the laser beam director, observed the interac-

tion delivering the laser-induced radiation to a grating-based

fiber spectrometer. The samples were exposed to laser radia-

tion until perforation while the spectrometer recorded spectra

every 10ms. The spectrometer system covered a spectrum

ranging from 200 nm to 1000 nm with an optical resolution

inferior than 0.8 nm.

Figure 3 presents typical spectra collected when the

HEL beam was incident on carbon steel (top) and aluminum

samples (bottom). The spectral components identified are

listed in the figure. At a first glance, we observe that the

spectra produced are different. Carbon steel (top) has strong

emissions between 550 nm and 650 nm, while aluminum has

emission between 450 nm and 550 nm. These spectral signa-

tures explain why the colour of the flames in Fig. 1(a) is blue

and orange in Fig. 1(b). As a rule of thumb, the broad spec-

tral features observed are attributed to molecular emitters,

while the sharp and narrow ones are attributed to excited

atoms. The detected background emission, which increases

from short to longer wavelengths, is mainly attributed to a

mixture of both blackbody thermal radiation and the ignited

particulate material ejected in the combustion plume.

Carbon steel is mainly composed of a mixture of iron

(Fe) and carbon (C). Fe oxidizes rapidly when immersed in an

oxygen-filled environment such as the atmosphere, more so

when heated to high temperatures. As Fe is the major constitu-

ent of carbon steel and the yield of C oxidation is much

weaker than that of Fe, only emissions from the transitional

system D5D4!X5D4 of iron oxides (FeO) have been observed.

FIG. 1. Color-calibrated pictures of a

HEL beam interacting with (a) alumi-

num and (b) carbon steel samples.

FIG. 2. Schematic representation of the experimental setup.

173102-2 Daigle, Pudo, and Th�eberge J. Appl. Phys. 122, 173102 (2017)

In addition to the intense FeO bands, the strongest Fe I and

Mn I heads have been identified. Manganese is normally

added to carbon steel to improve the workability and resis-

tance to wear. AISI 1020 contains approximately 0.5% of

manganese.

Aluminum oxide (AlO) fluorescence lines from the transi-

tional system B2Rþ!X2Rþ were observed when the alumi-

num sample (Fig. 3, bottom) was exposed to HEL radiation.

Magnesium is usually added to aluminum to improve mechan-

ical, fabrication, and welding characteristics. Even though

magnesium is found at approximately 1% in this type of alu-

minum, its high oxidation yield resulted in three distinct MgO

bands coming from the systems 3D ! 3P, D1D!A1P, and

B1R ! X1R. Al I atomic features were identified in the spec-

trum, as well as Mn I which is only present at 0.1% in this

type of aluminum. Na I and Li I emissions were also observed.

While it is very likely that the sample has been in contact with

contaminants containing sodium during fabrication, it was

unexpected to detect the lithium line. Lithium can be added to

aluminum to improve its strength and reduce its weight, creat-

ing an uncommon alloy mostly used in aeronautics. The 6061-

T6 aluminum grade is not known to contain lithium, and thus,

we speculate that the emission line probably originated from

trace contaminants present in the sample.

In order to test the sensitivity of the technique, the surface

of an aluminum plate was covered with a thin layer of white

aerosol paint that was let to dry overnight. The idea was to

verify whether HELIOS could be used to detect the presence

of the paint before the laser beam penetrated into the alumi-

num substrate. Figure 4 presents a typical spectrum captured

10ms after ignition of the laser. Immediately, the HEL beam

set the paint on fire, producing intense molecular bands shown

in the spectrum, most of them being attributed to titanium

oxide (TiO) C3D ! X3D and A3U ! X3D systems. Titanium

dioxide is a white substance often used as a pigment in paint.

Once the paint was ablated and burned from the area exposed

to the laser (<1 s), the spectrum captured by the spectrometer

rapidly evolved into the aluminum spectrum depicted at the

bottom of Fig. 3.

III. ANALYSIS AND DISCUSSION

Following this test campaign, it was decided to design a

detection and line identification software to verify whether

the technique could be viable in an autonomous stand-alone

spectroscopic system. A basic and straightforward approach

was adopted where software scans through all the spectra

captured during the entire engagement searching for peaks

present in the collected spectra. Those peaks are then com-

pared with a database to verify if they can be assigned to any

known atom or molecule. Among the atomic lines currently

included in the database, there are sodium (Na), potassium

(K), lithium (Li), aluminum (Al), magnesium (Mg), copper

(Cu), lead (Pb), manganese (Mn), calcium (Ca), and iron

(Fe). The molecular bands of interest identified are alumi-

num oxide (AlO), copper oxide (CuO), calcium oxide (CaO),

calcium hydroxide (CaOH), diatomic carbon (C2), iron oxide

(FeO), and magnesium oxide (MgO). A confidence level is

then calculated based on the accuracy of the peak wave-

length position and its spectral intensity relative to other

detected lines originating from the same atom/molecular spe-

cies. False detections are then identified and removed, leav-

ing only the detected lines that were successfully identified

and assigned.

The software was put to the test against a two-layer

metallic assembly consisting of a carbon steel plate mated to

an aluminum plate, with the thickness of both being

3.18mm. Once again, the HEL beam was set to 6 kW,

focused to an intensity of 7.5 kW/cm2, and irradiated the

sample until perforation. The spectrometer recorded spectra

every 10ms, and the software reviewed the collected infor-

mation searching its database for known atomic and molecu-

lar features.

The species identified during the whole process (over

3000 spectra) are Al, AlO, Fe, FeO, Li, MgO, Mn, and Na,

FIG. 3. Typical spectra collected during the interaction with carbon steel

(top) and aluminum (bottom).

FIG. 4. White aerosol paint spectrum.

173102-3 Daigle, Pudo, and Th�eberge J. Appl. Phys. 122, 173102 (2017)

including in fact all the species depicted in Fig. 3. For this

specific test, the software succeeded in labelling 98% of the

features that could be identified manually by human observa-

tion, 1.5% remained undetected, and 0.5% was misidentified.

The software completed the analysis of the 3000 spectra in

38 s, whereas it took 4 h for a trained spectroscopist to manu-

ally run through all the spectra. It is noteworthy to mention

that it is in the early stages of development, and there is

room for improvement in terms of peak detection and feature

identification.

Nonetheless, it remains a very useful tool in its actual

form as it is possible to rapidly plot the temporal evolution

of different spectral features and compare them one with

another. An example of such traces is shown in Fig. 5 where

the spectral intensity of the AlO system is plotted against

that of FeO. These were produced after the software ran

through all the spectra, indicating the intensity of the stron-

gest peak of the system detected and identified as either AlO

(top) or FeO (bottom).

After ignition of the laser, the carbon steel plate heated

rapidly, favoring the production of FeO, and hence, the

orange system was identified by the software for the first 3.6 s

of the engagement until it was no longer observed. This indi-

cates that the laser has completely drilled through the carbon

steel and is now starting to ablate the aluminum plate.

Incidentally, AlO emissions started to be detected at the

moment those from FeO were fading out. Initially very intense,

they remained undetected for close to 8 s after the laser reached

the aluminum surface. The strong AlO signals observed

between 3 s and 5 s are attributed to contaminants ejected from

the aluminum plate during the interaction with steel, which

increased the absorption of laser energy and stimulated the oxi-

dation process. Once the contaminants were consumed, the

AlO emissions halted until the metallic plate accumulated suf-

ficient heat to resume the oxidation process. Subsequently,

AlO was observed until the sample was perforated.

Since they behaved in a similar fashion, atomic lines

from excited aluminum and iron could have been used for

the analysis. In fact, the traces plotted by the software for

both Al I and Fe I systems revealed trends similar to those

depicted in Fig. 5. However, it was discovered that the oxide

systems are excited at lower temperatures than atomic transi-

tions, making them more readily observable. In addition, the

emission yield is significantly higher with molecular transi-

tions. As depicted in Fig. 3, not only do the oxide systems

reach higher peak intensities than the atomic Fe I and Al I

heads but also their spectral width is thousands times larger.

Consequently, observing the HEL-induced oxides during the

interaction will lead to enhanced sensitivity and operational

distances. It is important to note that due to the thermal con-

ductivity and absorption of the metallic samples, the scale of

the thermal excitation of atomic and molecular components

will depend on both the laser intensity and the diameter of

the interaction zone.22 Therefore, the relative emission from

different contaminants or atomic lines can change depending

on these laser parameters, which restrains the capacity to

quantify low concentration components by the thermal exci-

tation. In opposite, the thermal excitation allows an efficient

and straightforward identification of laser effects and target

main components, which are the key information required

for operational applications.

The above example demonstrates how HELIOS can be

used to gain real-time information on the interaction with the

distant sample. The technique can be used to increase the

operator’s awareness about what is happening at the interac-

tion site, providing information in real time on the composi-

tion of a potentially unknown object, the moment of

perforation of a surface or layer, the impact of the laser on

the object (heating or drilling?), etc. This information can be

analysed in real time using a software similar to the one dis-

cussed or preserved for later analysis by a team of experts.

IV. CONCLUSIONS

Standoff operation of HELIOS was successfully demon-

strated on aluminum and carbon steel plates. A multi-kW com-

mercial laser was focused on samples positioned 200m away,

while a spectroscopic receiver placed beside the HEL emitter

observed in real time the spectral content of the resulting flame.

Intense fingerprint signatures of HEL-induced iron, aluminum,

and magnesium oxides were observed. When an aluminum

plate was covered with a thin layer of white aerosol paint,

strong titanium oxide bands were observed for the brief period

it took the laser-induced flame to vaporize it. Consequently,

the operator can easily gather information on the interaction

simply by collecting and analysing the spectral content of the

flames produced.

Due to the high emission yield of molecular emitters,

HELIOS has the potential to reach km-level operation dis-

tances. Given that a 10-cm diameter receiver was sufficient

to detect intense oxide signals from 200m, extending the

range would simply involve increasing the aperture of the

receiver, using an amplified spectroscopic detector or by

ramping the HEL power up.

ACKNOWLEDGMENTS

This work was supported by the Defence Research and

Development Canada Program. The authors acknowledgeFIG. 5. Spectral intensity temporal evolution of the strongest AlO (top) and

FeO (bottom) lines.

173102-4 Daigle, Pudo, and Th�eberge J. Appl. Phys. 122, 173102 (2017)

the technical support from Mr. Pascal Duchesne and Mr.

Gaston Nadeau.

1A. C. Tam, “Laser-cleaning techniques for removal of surface partic-

ulates,” J. Appl. Phys. 71(7), 3515–3523 (1992).2J. M. Lee and K. G. Watkins, “Laser removal of oxides and particles from

copper surfaces for microelectronic fabrication,” Opt. Express 7(2), 68–76(2000).

3W. Schulz, U. Eppelt, and R. Poprawe, “Review on laser drilling I.

Fundamentals, modeling, and simulation,” J. Laser Appl. 25, 012006 (2013).4J. Lu and V. Kujanp€a€a, “Review study on remote laser welding with fiber

lasers,” J. Laser Appl. 25, 052008 (2013).5M. Zhang, G. Chen, Y. Zhou, and S. Liao, “Optimization of deep penetra-

tion laser welding of thick stainless steel with a 10 kW fiber laser,” Mater.

Des. 53, 568–576 (2014).6K. A. Ghany and M. Newishy, “Cutting of 1.2mm thick austenitic stain-

less steel sheet using pulsed and CW Nd: YAG laser,” J. Mater. Process

Technol. 168(3), 438–447 (2005).7D. J. Richardson, J. Nilsson, and W. A. Clarkson, “High power fiber lasers:

Current status and future perspectives,” J. Opt. Soc. Am. B 27(11),B63–B92 (2010).8V. Coffey, “High-energy lasers: New advances in defense applications,”

Opt. Photonics News 25(10), 28–35 (2014).9T. Purtonen, A. Kalliosaari, and A. Salminen, “Monitoring and adaptive

control of laser processes,” Phys. Procedia 56, 1218– 1231 (2014).10A. Sun, E. Kannatey-Asibu, Jr., and M. Gartner, “Sensor systems for real-

time monitoring of laser weld quality,” J. Laser Appl. 11, 153 (1999).11V. N. Petrovskiy, N. M. Prokopova, P. Y. Shcheglov, A. P. Streltsov,

Y. A. Vdovin, and V. M. Yermachenko, “Detection of radiation of power-

ful fiber lasers reflected back from metals in course of laser processing,”

Laser Phys. Lett. 7, 396 (2010).12B. Verhoff, S. S. Harilal, J. R. Freeman, P. K. Diwakar, and A. Hassanein,

“Dynamics of femto- and nanosecond laser ablation plumes investigated

using optical emission spectroscopy,” J. Appl. Phys. 112, 093303 (2012).

13R. L. Fante, “Electromagnetic beam propagation in turbulent media,”

Proc. IEEE 63(12), 1669–1692 (1975).14L. Bissonnette, “Multiscattering model for propagation of narrow light

beams in aerosol media,” Appl. Opt. 27, 2478–2484 (1988).15L. Bradley and J. Herrmann, “Phase compensation for thermal blooming,”

Appl. Opt. 13, 331–334 (1974).16R. N. Clark and T. L. Roush, “Reflectance spectroscopy: Quantitative

analysis techniques for remote sensing applications,” J. Geophys. Res.

89(B7), 6329–6340, https://doi.org/10.1029/JB089iB07p06329 (1984).17Y. Saito, K. Hatake, E. Nomura, T. D. Kawahara, A. Nomura, N.

Sugimoto, and T. Itabe, “Range-resolved image detection of laser-induced

fluorescence of natural trees for vegetation distribution monitoring,” Jpn.

J. Appl. Phys., Part 1 36(11), 7024 (1997).18K. Pathak, R. Kumar, V. K. Singh, R. Agrawal, S. Rai, and A. K. Rai,

“Assessment of LIBS for spectrochemical analysis: A review,” Appl.

Spectrosc. Rev. 47(1), 14–40 (2012).19S. Palanco, M. Klassen, J. Skupin, K. Hansen, E. Schubert, G. Sepold,

and J. J. Laserna, “Spectroscopic diagnostics on CW-laser welding plas-

mas of aluminum alloys,” Spectrochim. Acta, Part B 56(6), 651–659

(2001).20B. Sall�e, D. A. Cremers, S. Maurice, R. C. Wiens, and P. Fichet,

“Evaluation of a compact spectrograph for in-situ and stand-off laser-

induced breakdown spectroscopy analyses of geological samples on Mars

missions,” Spectrochim. Acta, Part B 60(6), 805–815 (2005).21J.-F. Daigle, G. M�ejean, W. Liu, F. Th�eberge, H. L. Xu, Y. Kamali, J.

Bernhardt, A. Azarm, Q. Sun, P. Mathieu, G. Roy, J.-R. Simard, and S. L.

Chin, “Long range trace detection in aqueous aerosol using remote

filament-induced breakdown spectroscopy,” Appl. Phys. B 87(4), 749–754(2007).

22J.-F. Daigle, D. Pudo, F. Th�eberge, and J. Fortin, “Spectroscopic monitor-

ing of FeO fluorescence for laser treatment of steel surfaces in air,”

J. Laser Appl. 27(3), 032005 (2015).23S. Goroshin, J. Mamen, A. Higgins, T. Bazyn, N. Glumac, and H. Krier,

“Emission spectroscopy of flame fronts in aluminum suspensions,” Proc.

Combust. Inst. 31(2), 2011–2019 (2007).

173102-5 Daigle, Pudo, and Th�eberge J. Appl. Phys. 122, 173102 (2017)

CAN UNCLASSIFIED

CAN UNCLASSIFIED

DOCUMENT CONTROL DATA (Security markings for the title, abstract and indexing annotation must be entered when the document is Classified or Designated)

1. ORIGINATOR (The name and address of the organization preparing the document. Organizations for whom the document was prepared, e.g., Centre sponsoring a contractor's report, or tasking agency, are entered in Section 8.) DRDC – Valcartier Research Centre Defence Research and Development Canada 2459 route de la Bravoure Quebec (Quebec) G3J 1X5 Canada

2a. SECURITY MARKING (Overall security marking of the document including special supplemental markings if applicable.)

CAN UNCLASSIFIED

2b. CONTROLLED GOODS

NON-CONTROLLED GOODS DMC A

3. TITLE (The complete document title as indicated on the title page. Its classification should be indicated by the appropriate abbreviation (S, C or U) in parentheses after the title.) Standoff High Energy Laser Induced Oxidation Spectroscopy (HELIOS)

4. AUTHORS (last name, followed by initials – ranks, titles, etc., not to be used) Daigle, J.-F.; Pudo, D.; Théberge, F.

5. DATE OF PUBLICATION (Month and year of publication of document.) November 2017

6a. NO. OF PAGES (Total containing information, including Annexes, Appendices, etc.)

5

6b. NO. OF REFS (Total cited in document.)

23 7. DESCRIPTIVE NOTES (The category of the document, e.g., technical report, technical note or memorandum. If appropriate, enter the type of report,

e.g., interim, progress, summary, annual or final. Give the inclusive dates when a specific reporting period is covered.) External Literature (P)

8. SPONSORING ACTIVITY (The name of the department project office or laboratory sponsoring the research and development – include address.) DRDC – Valcartier Research Centre Defence Research and Development Canada 2459 route de la Bravoure Quebec (Quebec) G3J 1X5 Canada

9a. PROJECT OR GRANT NO. (If appropriate, the applicable research and development project or grant number under which the document was written. Please specify whether project or grant.)

9b. CONTRACT NO. (If appropriate, the applicable number under which the document was written.)

10a. ORIGINATOR’S DOCUMENT NUMBER (The official document number by which the document is identified by the originating activity. This number must be unique to this document.) DRDC-RDDC-2017-P092

10b. OTHER DOCUMENT NO(s). (Any other numbers which may be assigned this document either by the originator or by the sponsor.)

11a. FUTURE DISTRIBUTION (Any limitations on further dissemination of the document, other than those imposed by security classification.)

Public release

11b. FUTURE DISTRIBUTION OUTSIDE CANADA (Any limitations on further dissemination of the document, other than those imposed by security classification.)

CAN UNCLASSIFIED

CAN UNCLASSIFIED

12. ABSTRACT (A brief and factual summary of the document. It may also appear elsewhere in the body of the document itself. It is highly desirable that the abstract of classified documents be unclassified. Each paragraph of the abstract shall begin with an indication of the security classification of the information in the paragraph (unless the document itself is unclassified) represented as (S), (C), (R), or (U). It is not necessary to include here abstracts in both official languages unless the text is bilingual.) High Energy Lasers (HELs) used for defense applications require operational distances ranging from few hundred meters to several kilometers. As the distance increases, the incident beam properties and, consequently, the anticipated effect delivered to the sample become less predictable. Therefore, the direct observation of the event induced by the laser can become an asset. In this paper, we propose a novel spectroscopic method that analyses in real time the spectral components present in the flames produced during the interaction of a HEL with a metallic piece at a long distance. This method was used on aluminum and carbon steel samples placed 200m away from the laser system. It was discovered that the aluminum and iron oxides created as a by-product of the HEL reaction with the samples emitted clear fingerprint signatures that could be detected remotely using a spectroscopic receiver placed beside the HEL beam director. The real-time assessment of the laser-induced effect can be achieved by monitoring the temporal evolution of the oxide signatures, hence providing information to the operator about the reaction and the nature of the sample illuminated. ___________________________________________________________________________

13. KEYWORDS, DESCRIPTORS or IDENTIFIERS (Technically meaningful terms or short phrases that characterize a document and could be helpful in cataloguing the document. They should be selected so that no security classification is required. Identifiers, such as equipment model designation, trade name, military project code name, geographic location may also be included. If possible keywords should be selected from a published thesaurus, e.g., Thesaurus of Engineering and Scientific Terms (TEST) and that thesaurus identified. If it is not possible to select indexing terms which are Unclassified, the classification of each should be indicated as with the title.) High energy laser, spectroscopy, metal